The robot arm systems are the most target systems in the fields of faults detection and diagnosis which are electrical and the mechanical systems in many fields. Fault detection and diagnosis study is presented for two robot arms. The disturbance due to the faults at robot's joints causes oscillations at the tip of the robot arm. The acceleration in multi-direction is analysed to extract the features of the faults. Simulations for planar and space robots are presented. Two types of feature (faults) detection methods are used in this paper. The first one is the discrete wavelet transform, which is applied in many research's works before. The second type, is the Slantlet transform, which represents an improved model of the discrete wavelet transform. The multi-layer perceptron artificial neural network is used for the purpose of faults allocation and classification. According to the obtained results, the Slantlet transform with the multi-layer perceptron artificial neural network appear to possess best performance (4.7088e-05), lower consuming time
(71.017308 sec) and higher accuracy (100%) than the results obtained when applying discrete wavelet transform and artificial neural network for the same purpose.
Development of a Condition Monitoring Algorithm for Industrial Robots based o...IJECEIAES
Signal processing plays a significant role in building any condition monitoring system. Many types of signals can be used for condition monitoring of machines, such as vibration signals, as in this research; and processing these signals in an appropriate way is crucial in extracting the most salient features related to different fault types. A number of signal processing techniques can fulfil this purpose, and the nature of the captured signal is a significant factor in the selection of the appropriate technique. This chapter starts with a discussion of the proposed robot condition monitoring algorithm. Then, a consideration of the signal processing techniques which can be applied in condition monitoring is carried out to identify their advantages and disadvantages, from which the time-domain and discrete wavelet transform signal analysis are selected.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical vehicle. Like failures of a position sensor, a voltage sensor, and current sensors. Three-phase induction motors are the “workhorses” of industry and are the most widely used electrical machines. This paper presents a scheme for Fault Detection and Isolation (FDI). The proposed approach is a sensor-based technique using the mains current measurement. Current sensors are widespread in power converters control and in electrical drives. Thus, to ensure continuous operation with reconfiguration control, a fast sensor fault detection and isolation is required. In this paper, a new and fast faulty current sensor detection and isolation is presented. It is derived from intelligent techniques. The main interest of field programmable gate array is the extremely fast computation capabilities. That allows a fast residual generation when a sensor fault occurs. Using of Xilinx System Generator in Matlab / Simulink allows the real-time simulation and implemented on a field programmable gate array chip without any VHSIC Hardware Description Language coding. The sensor fault detection and isolation algorithm was implemented targeting a Virtex5. Simulation results are given to demonstrate the efficiency of this FDI approach.
State and fault estimation based on fuzzy observer for a class of Takagi-Suge...IJEECSIAES
Singular nonlinear systems have received wide attention in recent years, and can be found in various applications of engineering practice. On the basis of the Takagi-Sugeno (T-S) formalism, which represents a powerful tool allowing the study and the treatment of nonlinear systems, many control and diagnostic problems have been treated in the literature. In this work, we aim to present a new approach making it possible to estimate simultaneously both non-measurable states and unknown faults in the actuators and sensors for a class of continuous-time Takagi-Sugeno singular model (CTSSM). Firstly, the considered class of CTSSM is represented in the case of premise variables which are non-measurable, and is subjected to actuator and sensor faults. Secondly, the suggested observer is synthesized based on the decomposition approach. Next, the observer’s gain matrices are determined using the Lyapunov theory and the constraints are defined as linear matrix inequalities (LMIs). Finally, a numerical simulation on an application example is given to demonstrate the usefulness and the good performance of the proposed dynamic system.
State and fault estimation based on fuzzy observer for a class of Takagi-Suge...nooriasukmaningtyas
Singular nonlinear systems have received wide attention in recent years, and can be found in various applications of engineering practice. On the basis of the Takagi-Sugeno (T-S) formalism, which represents a powerful tool allowing the study and the treatment of nonlinear systems, many control and diagnostic problems have been treated in the literature. In this work, we aim to present a new approach making it possible to estimate simultaneously both non-measurable states and unknown faults in the actuators and sensors for a class of continuous-time Takagi-Sugeno singular model (CTSSM). Firstly, the considered class of CTSSM is represented in the case of premise variables which are non-measurable, and is subjected to actuator and sensor faults. Secondly, the suggested observer is synthesized based on the decomposition approach. Next, the observer’s gain matrices are determined using the Lyapunov theory and the constraints are defined as linear matrix inequalities (LMIs). Finally, a numerical simulation on an application example is given to demonstrate the usefulness and the good performance of the proposed dynamic system.
Distributed Cooperative Fault Diagnosis Method for Internal Components of Rob...CSCJournals
Robot systems have recently been studied for real world situations such as space exploration, underwater inspection, and disaster response. In extreme environments, a robot system has a probability of failure. Therefore, considering fault tolerance is important for mission success. In this study, we proposed a distributed cooperative fault diagnosis method for internal components of robot systems. This method uses diagnostic devices called diagnosers to observe the state of an electrical component. These diagnosers execute each diagnosis independently and in parallel with one another, and it is assumed that they are interconnected through wireless communication. A fault diagnosis technique was proposed that involves gathering the diagnosis results. Further, computer simulations confirmed that the distributed cooperative fault diagnosis method could detect component faults in simplified fault situations.
Design and implementation of Arduino based robotic armIJECEIAES
This study presents the model, design, and construction of the Arduino based robotic arm, which functions across a distance as it is controlled through a mobile application. A six degree of freedom robotic arm has been designed and implemented for the purpose of this research. The design controlled by the Arduino platform receives orders from the user’s mobile application through wireless controlling signals, that is Bluetooth. The arm is made up of five rotary joints and an end effector, where rotary motion is provided by the servomotor. Each link has been first designed using solid works and then printed by 3D printer. The assembly of the parts of the robot and the motor’s mechanical shapes produce the final prototype of the arm. The Arduino has been programmed to provide rotation to each corresponding servo motor to the sliders in the designed mobile application for usage from distance.
Development of a Condition Monitoring Algorithm for Industrial Robots based o...IJECEIAES
Signal processing plays a significant role in building any condition monitoring system. Many types of signals can be used for condition monitoring of machines, such as vibration signals, as in this research; and processing these signals in an appropriate way is crucial in extracting the most salient features related to different fault types. A number of signal processing techniques can fulfil this purpose, and the nature of the captured signal is a significant factor in the selection of the appropriate technique. This chapter starts with a discussion of the proposed robot condition monitoring algorithm. Then, a consideration of the signal processing techniques which can be applied in condition monitoring is carried out to identify their advantages and disadvantages, from which the time-domain and discrete wavelet transform signal analysis are selected.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical vehicle. Like failures of a position sensor, a voltage sensor, and current sensors. Three-phase induction motors are the “workhorses” of industry and are the most widely used electrical machines. This paper presents a scheme for Fault Detection and Isolation (FDI). The proposed approach is a sensor-based technique using the mains current measurement. Current sensors are widespread in power converters control and in electrical drives. Thus, to ensure continuous operation with reconfiguration control, a fast sensor fault detection and isolation is required. In this paper, a new and fast faulty current sensor detection and isolation is presented. It is derived from intelligent techniques. The main interest of field programmable gate array is the extremely fast computation capabilities. That allows a fast residual generation when a sensor fault occurs. Using of Xilinx System Generator in Matlab / Simulink allows the real-time simulation and implemented on a field programmable gate array chip without any VHSIC Hardware Description Language coding. The sensor fault detection and isolation algorithm was implemented targeting a Virtex5. Simulation results are given to demonstrate the efficiency of this FDI approach.
State and fault estimation based on fuzzy observer for a class of Takagi-Suge...IJEECSIAES
Singular nonlinear systems have received wide attention in recent years, and can be found in various applications of engineering practice. On the basis of the Takagi-Sugeno (T-S) formalism, which represents a powerful tool allowing the study and the treatment of nonlinear systems, many control and diagnostic problems have been treated in the literature. In this work, we aim to present a new approach making it possible to estimate simultaneously both non-measurable states and unknown faults in the actuators and sensors for a class of continuous-time Takagi-Sugeno singular model (CTSSM). Firstly, the considered class of CTSSM is represented in the case of premise variables which are non-measurable, and is subjected to actuator and sensor faults. Secondly, the suggested observer is synthesized based on the decomposition approach. Next, the observer’s gain matrices are determined using the Lyapunov theory and the constraints are defined as linear matrix inequalities (LMIs). Finally, a numerical simulation on an application example is given to demonstrate the usefulness and the good performance of the proposed dynamic system.
State and fault estimation based on fuzzy observer for a class of Takagi-Suge...nooriasukmaningtyas
Singular nonlinear systems have received wide attention in recent years, and can be found in various applications of engineering practice. On the basis of the Takagi-Sugeno (T-S) formalism, which represents a powerful tool allowing the study and the treatment of nonlinear systems, many control and diagnostic problems have been treated in the literature. In this work, we aim to present a new approach making it possible to estimate simultaneously both non-measurable states and unknown faults in the actuators and sensors for a class of continuous-time Takagi-Sugeno singular model (CTSSM). Firstly, the considered class of CTSSM is represented in the case of premise variables which are non-measurable, and is subjected to actuator and sensor faults. Secondly, the suggested observer is synthesized based on the decomposition approach. Next, the observer’s gain matrices are determined using the Lyapunov theory and the constraints are defined as linear matrix inequalities (LMIs). Finally, a numerical simulation on an application example is given to demonstrate the usefulness and the good performance of the proposed dynamic system.
Distributed Cooperative Fault Diagnosis Method for Internal Components of Rob...CSCJournals
Robot systems have recently been studied for real world situations such as space exploration, underwater inspection, and disaster response. In extreme environments, a robot system has a probability of failure. Therefore, considering fault tolerance is important for mission success. In this study, we proposed a distributed cooperative fault diagnosis method for internal components of robot systems. This method uses diagnostic devices called diagnosers to observe the state of an electrical component. These diagnosers execute each diagnosis independently and in parallel with one another, and it is assumed that they are interconnected through wireless communication. A fault diagnosis technique was proposed that involves gathering the diagnosis results. Further, computer simulations confirmed that the distributed cooperative fault diagnosis method could detect component faults in simplified fault situations.
Design and implementation of Arduino based robotic armIJECEIAES
This study presents the model, design, and construction of the Arduino based robotic arm, which functions across a distance as it is controlled through a mobile application. A six degree of freedom robotic arm has been designed and implemented for the purpose of this research. The design controlled by the Arduino platform receives orders from the user’s mobile application through wireless controlling signals, that is Bluetooth. The arm is made up of five rotary joints and an end effector, where rotary motion is provided by the servomotor. Each link has been first designed using solid works and then printed by 3D printer. The assembly of the parts of the robot and the motor’s mechanical shapes produce the final prototype of the arm. The Arduino has been programmed to provide rotation to each corresponding servo motor to the sliders in the designed mobile application for usage from distance.
Evolutionary Design of Mathematical tunable FPGA Based MIMO Fuzzy Estimator S...Waqas Tariq
In this research, a Multi Input Multi Output (MIMO) position Field Programmable Gate Array (FPGA)-based fuzzy estimator sliding mode control (SMC) design with the estimation laws derived in Lyapunov sense and application to robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy inference methodology and Lyapunov based method, the controllers output has improved. The main target in this research is analyses and design of the position MIMO artificial Lyapunov FPGA-based controller for robot manipulator in order to solve uncertainty, external disturbance, nonlinear equivalent part, chattering phenomenon, time to market and controller size using FPGA. Robot manipulators are nonlinear, time variant and a number of parameters are uncertain therefore design robust and stable controller based on Lyapunov based is discussed in this research. Studies about classical sliding mode controller (SMC) show that: although this controller has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. The first challenge; nonlinear dynamic part; is applied by inference estimator method in sliding mode controller in order to solve the nonlinear problems in classical sliding mode controller. And the second challenge; chattering phenomenon; is removed by linear method. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov. In the last part it can find the implementation of MIMO fuzzy estimator sliding mode controller on FPGA; FPGA-based fuzzy estimator sliding mode controller has many advantages such as high speed, low cost, short time to market and small device size. One of the most important drawbacks is limited capacity of available cells which this research focuses to solve this challenge. FPGA can be used to design a controller in a single chip Integrated Circuit (IC). In this research the SMC is designed using Very High Description Language (VHDL) for implementation on FPGA device (XA3S1600E-Spartan-3E), with minimum chattering.
Robust Fault Detection and Isolation using Bond Graph for an Active-Passive V...CSCJournals
A robot is a complex machine, comprising mechanism, actuators, sensors, and electrical system. It is, therefore, hard to guarantee that all the components can always function normally. If one component fails, the robot might harm humans. In order to develop the active-passive variable serial elastic actuator (APVSEA) [1] that can detect the occurrence of any component fault, this paper uses bond graph to design a robust fault detection and isolation (RFDI) system. When the robot components malfunction, the RFDI system will execute suitable isolation strategies to guarantee human safety and use zero-gravity control (ZGC) to simultaneously compensate for the torque caused by gravity. Thus, the user can consistently interact with the robot easily and safely. From the experimental results, the RFDI system can filter out uncertain parameters and identify the failed component. In addition, the zero-gravity control can lessen potentially physical damage to humans.
Mathematical modeling and kinematic analysis of 5 degrees of freedom serial l...IJECEIAES
Modeling and kinematic analysis are crucial jobs in robotics that entail identifying the position of the robot’s joints in order to accomplish particular tasks. This article uses an algebraic approach to model the kinematics of a serial link, 5 degrees of freedom (DOF) manipulator. The analytical method is compared to an optimization strategy known as sequential least squares programming (SLSQP). Using an Intel RealSense 3D camera, the colored object is picked up and placed using vision-based technology, and the pixel location of the object is translated into robot coordinates. The LOBOT LX15D serial bus servo controller was used to transmit these coordinates to the robotic arm. Python3 programming language was used throughout the entire analysis. The findings demonstrated that both analytical and optimized inverse kinematic solutions correctly identified colored objects and positioned them in their appropriate goal points.
Detection of internal and external faults of single-phase induction motor usi...IJECEIAES
The main aim of this work is to analyze the input current waveform for a single-phase induction capacitor-run motor (SIMCR) to detect the faults. Internal and external faults were applied to the SIMCR and the current was measured. An armature (broken rotor bar) and bearing faults were applied to the SIMCR. A microcontroller was used to record the motor current signal and MATLAB software was used to analyze it with the different types of fault with varying load operations. Various values of the running capacitor were used to investigate the effect of these values on the wave-current shape. Total harmonic distortion (THD) for the voltage and current was measured. A deep demonstration of the experimental results was also provided for a better understanding of the mechanisms of bearing and armature faults (broken rotor bars) and the vibration was recorded. Spectral and power analyses revealed the difference in total harmonic distortion. The proposed method in this paper can be used in various industrial applications and this technique is quite cheap and helps most of the researchers and very effectual.
Design and development of touch screen controlled stairs climbing roboteSAT Journals
Abstract This paper presents a method of developing a stairs climbing robot with self balancing chair mounted on the top of the robot. It is one of the major task in the field of Mechatronics require a mechanical arrangement and electronics based control of the actuators using wireless technology. In most of the mechanism it is hard to maintain the slope position of the seat while carrying some goods on it, so taking in action all these condition the robot is to design and develop [1] which will climb on the stairs and adjust themselves as per environmental condition. Keywords:- Accelerometer, CC2500, Touch Screen, Microcontroller, Relays
Fractional-order sliding mode controller for the two-link robot arm IJECEIAES
This study presents a control system of the two-link robot arm based on the sliding mode controller with the fractional-order. Firstly, the equations of the two-link robot arm are analyzed, then the author proposes the controller for each joint based on these equations. The controller is a sliding mode controller with its order is not an integer value. The task of the control system is controlling the torques acted on the joints so that the response angle of each link equal to the desired angle. The effectiveness of the proposed control system is demonstrated through Matlab-Simulink software. The robot model and controller are built for investigating the efficiency of the system. The result shows that the system quality is very good: there is not the chattering phenomenon of torques, the response angle of two links always follow the desired angle with the short transaction time and the static error of zero.
Balancing a Segway robot using LQR controller based on genetic and bacteria f...TELKOMNIKA JOURNAL
A two-wheeled single seat Segway robot is a special kind of wheeled mobile robot, using it as a human transporter system needs applying a robust control system to overcome its inherent unstable problem. The mathematical model of the system dynamics is derived and then state space formulation for the system is presented to enable design state feedback controller scheme. In this research, an optimal control system based on linear quadratic regulator (LQR) technique is proposed to stabilize the mobile robot. The LQR controller is designed to control the position and yaw rotation of the two-wheeled vehicle. The proposed balancing robot system is validated by simulating the LQR using Matlab software. Two tuning methods, genetic algorithm (GA) and bacteria foraging optimization algorithm (BFOA) are used to obtain optimal values for controller parameters. A comparison between the performance of both controllers GA-LQR and BFO-LQR is achieved based on the standard control criteria which includes rise time, maximum overshoot, settling time and control input of the system. Simulation results suggest that the BFOA-LQR controller can be adopted to balance the Segway robot with minimal overshoot and oscillation frequency.
Fault diagnosis of rolling element bearings using artificial neural network IJECEIAES
Bearings are essential components in the most electrical equipment. Procedures for monitoring the condition of bearings must be developed to prevent unexpected failure of these components during operation to avoid costly consequences. In this paper, the design of a monitoring system for the detection of rolling element-bearings failure is proposed. The method for detecting and locating this type of fault is carried out using advanced intelligent techniques based on a perceptron multilayer artificial neural network (MLP-ANN); its database uses statistical indicators characterizing vibration signals. The effectiveness of the proposed method is illustrated using experimentally obtained bearing vibration data, and the results have shown good accuracy in detecting and locating defects.
Obstacle Avoiding Robot
Robotics is a branch of science that deals with Mechanical, Electrical and Software fields. Robots are the machines that are used in our day-to-day to life to reduce men power and work accurately without any distortions. Robots can be classified into two different sections basing upon their skills as Automated and Manual. Obstacle detector is a Automated robot which itself recognizes the obstacle in its path and moves in free direction. Robot detects the obstacle by using two IR Sensors placed in front.
The IR sensors are placed on left and right side of the robot through which continuous Infrared radiation is emitted for detection of obstacles in the path. These IR Sensors are connected to a controlling element AT89c51 µc. When a obstacle is placed in the path of robot IR beam is reflected to the sensor from the obstacle. On detecting obstacle in the path sensor sends 0 volts to µc. This 0 voltage is detected by Microcontroller which avoids the obstacle by taking left or right turn. Similarly if the sensor sends +5v to Microcontroller, the Microcontroller assumes it as clear path and makes the robot to move in straight.
Two motors namely right motor and left motor are connected to Motor driver IC (L293D). L293D is interface with Microcontroller. Microcontroller sends logic 0 & logic 1 as per the programming to driver IC which makes motors to rotate in clockwise and anticlockwise direction. Wheels attached to the motors rotate accordingly with the motor shaft causing in the moment of the robot by wheels. In front portion of the robot a free wheel is attached to move the robot easily in any direction as per the requirement.
A 12Volts DC battery is attached to the circuit. As the microcontroller and sensors requires only 5v, set of resistors and capacitors are used to supply 5v DC to them. Power Management System is not maintained in the circuit as the battery can be removed after the usage of robot. So it does not cause any loss in the power of battery.
This type of robots has multiple applications in various fields. They can be used to know the strength of the opposite army in defense system. They can be used as floor and wall cleaners. They are used in automated GPS vehicles to calculate the moment of the vehicle overhead. These robots are easy to construct and cheaper in cost with long durability.
Smart element aware gate controller for intelligent wheeled robot navigationIJECEIAES
The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the proposed mechanism is very efficient in terms of providing shortest distance to reach the goal with maximum velocity as compared with the MENN. Specifically, the MEEG is better than MENN in minimizing the error rate by 58.33%.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
Sliding mode control-based system for the two-link robot armIJECEIAES
In this research, the author presents the model of the two-link robot arm and its dynamic equations. Based on these dynamic equations, the author builds the sliding mode controller for each joint of the robot. The tasks of the controllers are controlling the Torque in each Joint of the robot in order that the angle coordinates of each link coincide with the desired values. The proposed algorithm and robot model are built on Matlab-Simulink to investigate the system quality. The results show that the quality of the control system is very high: the response angles of each link quickly reach the desired values, and the static error equal to zero.
Development of depth map from stereo images using sum of absolute differences...nooriasukmaningtyas
This article proposes a framework for the depth map reconstruction using stereo images. Fundamentally, this map provides an important information which commonly used in essential applications such as autonomous vehicle navigation, drone’s navigation and 3D surface reconstruction. To develop an accurate depth map, the framework must be robust against the challenging regions of low texture, plain color and repetitive pattern on the input stereo image. The development of this map requires several stages which starts with matching cost calculation, cost aggregation, optimization and refinement stage. Hence, this work develops a framework with sum of absolute difference (SAD) and the combination of two edge preserving filters to increase the robustness against the challenging regions. The SAD convolves using block matching technique to increase the efficiency of matching process on the low texture and plain color regions. Moreover, two edge preserving filters will increase the accuracy on the repetitive pattern region. The results show that the proposed method is accurate and capable to work with the challenging regions. The results are provided by the Middlebury standard dataset. The framework is also efficiently and can be applied on the 3D surface reconstruction. Moreover, this work is greatly competitive with previously available methods.
Model predictive controller for a retrofitted heat exchanger temperature cont...nooriasukmaningtyas
This paper aims to demonstrate the practical aspects of process control theory for undergraduate students at the Department of Chemical Engineering at the University of Bahrain. Both, the ubiquitous proportional integral derivative (PID) as well as model predictive control (MPC) and their auxiliaries were designed and implemented in a real-time framework. The latter was realized through retrofitting an existing plate-and-frame heat exchanger unit that has been operated using an analog PID temperature controller. The upgraded control system consists of a personal computer (PC), low-cost signal conditioning circuit, national instruments USB 6008 data acquisition card, and LabVIEW software. LabVIEW control design and simulation modules were used to design and implement the PID and MPC controllers. The performance of the designed controllers was evaluated while controlling the outlet temperature of the retrofitted plate-and-frame heat exchanger. The distinguished feature of the MPC controller in handling input and output constraints was perceived in real-time. From a pedagogical point of view, realizing the theory of process control through practical implementation was substantial in enhancing the student’s learning and the instructor’s teaching experience.
More Related Content
Similar to Slantlet transform used for faults diagnosis in robot arm
Evolutionary Design of Mathematical tunable FPGA Based MIMO Fuzzy Estimator S...Waqas Tariq
In this research, a Multi Input Multi Output (MIMO) position Field Programmable Gate Array (FPGA)-based fuzzy estimator sliding mode control (SMC) design with the estimation laws derived in Lyapunov sense and application to robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy inference methodology and Lyapunov based method, the controllers output has improved. The main target in this research is analyses and design of the position MIMO artificial Lyapunov FPGA-based controller for robot manipulator in order to solve uncertainty, external disturbance, nonlinear equivalent part, chattering phenomenon, time to market and controller size using FPGA. Robot manipulators are nonlinear, time variant and a number of parameters are uncertain therefore design robust and stable controller based on Lyapunov based is discussed in this research. Studies about classical sliding mode controller (SMC) show that: although this controller has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. The first challenge; nonlinear dynamic part; is applied by inference estimator method in sliding mode controller in order to solve the nonlinear problems in classical sliding mode controller. And the second challenge; chattering phenomenon; is removed by linear method. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov. In the last part it can find the implementation of MIMO fuzzy estimator sliding mode controller on FPGA; FPGA-based fuzzy estimator sliding mode controller has many advantages such as high speed, low cost, short time to market and small device size. One of the most important drawbacks is limited capacity of available cells which this research focuses to solve this challenge. FPGA can be used to design a controller in a single chip Integrated Circuit (IC). In this research the SMC is designed using Very High Description Language (VHDL) for implementation on FPGA device (XA3S1600E-Spartan-3E), with minimum chattering.
Robust Fault Detection and Isolation using Bond Graph for an Active-Passive V...CSCJournals
A robot is a complex machine, comprising mechanism, actuators, sensors, and electrical system. It is, therefore, hard to guarantee that all the components can always function normally. If one component fails, the robot might harm humans. In order to develop the active-passive variable serial elastic actuator (APVSEA) [1] that can detect the occurrence of any component fault, this paper uses bond graph to design a robust fault detection and isolation (RFDI) system. When the robot components malfunction, the RFDI system will execute suitable isolation strategies to guarantee human safety and use zero-gravity control (ZGC) to simultaneously compensate for the torque caused by gravity. Thus, the user can consistently interact with the robot easily and safely. From the experimental results, the RFDI system can filter out uncertain parameters and identify the failed component. In addition, the zero-gravity control can lessen potentially physical damage to humans.
Mathematical modeling and kinematic analysis of 5 degrees of freedom serial l...IJECEIAES
Modeling and kinematic analysis are crucial jobs in robotics that entail identifying the position of the robot’s joints in order to accomplish particular tasks. This article uses an algebraic approach to model the kinematics of a serial link, 5 degrees of freedom (DOF) manipulator. The analytical method is compared to an optimization strategy known as sequential least squares programming (SLSQP). Using an Intel RealSense 3D camera, the colored object is picked up and placed using vision-based technology, and the pixel location of the object is translated into robot coordinates. The LOBOT LX15D serial bus servo controller was used to transmit these coordinates to the robotic arm. Python3 programming language was used throughout the entire analysis. The findings demonstrated that both analytical and optimized inverse kinematic solutions correctly identified colored objects and positioned them in their appropriate goal points.
Detection of internal and external faults of single-phase induction motor usi...IJECEIAES
The main aim of this work is to analyze the input current waveform for a single-phase induction capacitor-run motor (SIMCR) to detect the faults. Internal and external faults were applied to the SIMCR and the current was measured. An armature (broken rotor bar) and bearing faults were applied to the SIMCR. A microcontroller was used to record the motor current signal and MATLAB software was used to analyze it with the different types of fault with varying load operations. Various values of the running capacitor were used to investigate the effect of these values on the wave-current shape. Total harmonic distortion (THD) for the voltage and current was measured. A deep demonstration of the experimental results was also provided for a better understanding of the mechanisms of bearing and armature faults (broken rotor bars) and the vibration was recorded. Spectral and power analyses revealed the difference in total harmonic distortion. The proposed method in this paper can be used in various industrial applications and this technique is quite cheap and helps most of the researchers and very effectual.
Design and development of touch screen controlled stairs climbing roboteSAT Journals
Abstract This paper presents a method of developing a stairs climbing robot with self balancing chair mounted on the top of the robot. It is one of the major task in the field of Mechatronics require a mechanical arrangement and electronics based control of the actuators using wireless technology. In most of the mechanism it is hard to maintain the slope position of the seat while carrying some goods on it, so taking in action all these condition the robot is to design and develop [1] which will climb on the stairs and adjust themselves as per environmental condition. Keywords:- Accelerometer, CC2500, Touch Screen, Microcontroller, Relays
Fractional-order sliding mode controller for the two-link robot arm IJECEIAES
This study presents a control system of the two-link robot arm based on the sliding mode controller with the fractional-order. Firstly, the equations of the two-link robot arm are analyzed, then the author proposes the controller for each joint based on these equations. The controller is a sliding mode controller with its order is not an integer value. The task of the control system is controlling the torques acted on the joints so that the response angle of each link equal to the desired angle. The effectiveness of the proposed control system is demonstrated through Matlab-Simulink software. The robot model and controller are built for investigating the efficiency of the system. The result shows that the system quality is very good: there is not the chattering phenomenon of torques, the response angle of two links always follow the desired angle with the short transaction time and the static error of zero.
Balancing a Segway robot using LQR controller based on genetic and bacteria f...TELKOMNIKA JOURNAL
A two-wheeled single seat Segway robot is a special kind of wheeled mobile robot, using it as a human transporter system needs applying a robust control system to overcome its inherent unstable problem. The mathematical model of the system dynamics is derived and then state space formulation for the system is presented to enable design state feedback controller scheme. In this research, an optimal control system based on linear quadratic regulator (LQR) technique is proposed to stabilize the mobile robot. The LQR controller is designed to control the position and yaw rotation of the two-wheeled vehicle. The proposed balancing robot system is validated by simulating the LQR using Matlab software. Two tuning methods, genetic algorithm (GA) and bacteria foraging optimization algorithm (BFOA) are used to obtain optimal values for controller parameters. A comparison between the performance of both controllers GA-LQR and BFO-LQR is achieved based on the standard control criteria which includes rise time, maximum overshoot, settling time and control input of the system. Simulation results suggest that the BFOA-LQR controller can be adopted to balance the Segway robot with minimal overshoot and oscillation frequency.
Fault diagnosis of rolling element bearings using artificial neural network IJECEIAES
Bearings are essential components in the most electrical equipment. Procedures for monitoring the condition of bearings must be developed to prevent unexpected failure of these components during operation to avoid costly consequences. In this paper, the design of a monitoring system for the detection of rolling element-bearings failure is proposed. The method for detecting and locating this type of fault is carried out using advanced intelligent techniques based on a perceptron multilayer artificial neural network (MLP-ANN); its database uses statistical indicators characterizing vibration signals. The effectiveness of the proposed method is illustrated using experimentally obtained bearing vibration data, and the results have shown good accuracy in detecting and locating defects.
Obstacle Avoiding Robot
Robotics is a branch of science that deals with Mechanical, Electrical and Software fields. Robots are the machines that are used in our day-to-day to life to reduce men power and work accurately without any distortions. Robots can be classified into two different sections basing upon their skills as Automated and Manual. Obstacle detector is a Automated robot which itself recognizes the obstacle in its path and moves in free direction. Robot detects the obstacle by using two IR Sensors placed in front.
The IR sensors are placed on left and right side of the robot through which continuous Infrared radiation is emitted for detection of obstacles in the path. These IR Sensors are connected to a controlling element AT89c51 µc. When a obstacle is placed in the path of robot IR beam is reflected to the sensor from the obstacle. On detecting obstacle in the path sensor sends 0 volts to µc. This 0 voltage is detected by Microcontroller which avoids the obstacle by taking left or right turn. Similarly if the sensor sends +5v to Microcontroller, the Microcontroller assumes it as clear path and makes the robot to move in straight.
Two motors namely right motor and left motor are connected to Motor driver IC (L293D). L293D is interface with Microcontroller. Microcontroller sends logic 0 & logic 1 as per the programming to driver IC which makes motors to rotate in clockwise and anticlockwise direction. Wheels attached to the motors rotate accordingly with the motor shaft causing in the moment of the robot by wheels. In front portion of the robot a free wheel is attached to move the robot easily in any direction as per the requirement.
A 12Volts DC battery is attached to the circuit. As the microcontroller and sensors requires only 5v, set of resistors and capacitors are used to supply 5v DC to them. Power Management System is not maintained in the circuit as the battery can be removed after the usage of robot. So it does not cause any loss in the power of battery.
This type of robots has multiple applications in various fields. They can be used to know the strength of the opposite army in defense system. They can be used as floor and wall cleaners. They are used in automated GPS vehicles to calculate the moment of the vehicle overhead. These robots are easy to construct and cheaper in cost with long durability.
Smart element aware gate controller for intelligent wheeled robot navigationIJECEIAES
The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the proposed mechanism is very efficient in terms of providing shortest distance to reach the goal with maximum velocity as compared with the MENN. Specifically, the MEEG is better than MENN in minimizing the error rate by 58.33%.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
Sliding mode control-based system for the two-link robot armIJECEIAES
In this research, the author presents the model of the two-link robot arm and its dynamic equations. Based on these dynamic equations, the author builds the sliding mode controller for each joint of the robot. The tasks of the controllers are controlling the Torque in each Joint of the robot in order that the angle coordinates of each link coincide with the desired values. The proposed algorithm and robot model are built on Matlab-Simulink to investigate the system quality. The results show that the quality of the control system is very high: the response angles of each link quickly reach the desired values, and the static error equal to zero.
Development of depth map from stereo images using sum of absolute differences...nooriasukmaningtyas
This article proposes a framework for the depth map reconstruction using stereo images. Fundamentally, this map provides an important information which commonly used in essential applications such as autonomous vehicle navigation, drone’s navigation and 3D surface reconstruction. To develop an accurate depth map, the framework must be robust against the challenging regions of low texture, plain color and repetitive pattern on the input stereo image. The development of this map requires several stages which starts with matching cost calculation, cost aggregation, optimization and refinement stage. Hence, this work develops a framework with sum of absolute difference (SAD) and the combination of two edge preserving filters to increase the robustness against the challenging regions. The SAD convolves using block matching technique to increase the efficiency of matching process on the low texture and plain color regions. Moreover, two edge preserving filters will increase the accuracy on the repetitive pattern region. The results show that the proposed method is accurate and capable to work with the challenging regions. The results are provided by the Middlebury standard dataset. The framework is also efficiently and can be applied on the 3D surface reconstruction. Moreover, this work is greatly competitive with previously available methods.
Model predictive controller for a retrofitted heat exchanger temperature cont...nooriasukmaningtyas
This paper aims to demonstrate the practical aspects of process control theory for undergraduate students at the Department of Chemical Engineering at the University of Bahrain. Both, the ubiquitous proportional integral derivative (PID) as well as model predictive control (MPC) and their auxiliaries were designed and implemented in a real-time framework. The latter was realized through retrofitting an existing plate-and-frame heat exchanger unit that has been operated using an analog PID temperature controller. The upgraded control system consists of a personal computer (PC), low-cost signal conditioning circuit, national instruments USB 6008 data acquisition card, and LabVIEW software. LabVIEW control design and simulation modules were used to design and implement the PID and MPC controllers. The performance of the designed controllers was evaluated while controlling the outlet temperature of the retrofitted plate-and-frame heat exchanger. The distinguished feature of the MPC controller in handling input and output constraints was perceived in real-time. From a pedagogical point of view, realizing the theory of process control through practical implementation was substantial in enhancing the student’s learning and the instructor’s teaching experience.
Control of a servo-hydraulic system utilizing an extended wavelet functional ...nooriasukmaningtyas
Servo-hydraulic systems have been extensively employed in various industrial applications. However, these systems are characterized by their highly complex and nonlinear dynamics, which complicates the control design stage of such systems. In this paper, an extended wavelet functional link neural network (EWFLNN) is proposed to control the displacement response of the servo-hydraulic system. To optimize the controller's parameters, a recently developed optimization technique, which is called the modified sine cosine algorithm (M-SCA), is exploited as the training method. The proposed controller has achieved remarkable results in terms of tracking two different displacement signals and handling external disturbances. From a comparative study, the proposed EWFLNN controller has attained the best control precision compared with those of other controllers, namely, a proportional-integralderivative (PID) controller, an artificial neural network (ANN) controller, a wavelet neural network (WNN) controller, and the original wavelet functional link neural network (WFLNN) controller. Moreover, compared to the genetic algorithm (GA) and the original sine cosine algorithm (SCA), the M-SCA has shown better optimization results in finding the optimal values of the controller's parameters.
Decentralised optimal deployment of mobile underwater sensors for covering la...nooriasukmaningtyas
This paper presents the problem of sensing coverage of layers of the ocean in three dimensional underwater environments. We propose distributed control laws to drive mobile underwater sensors to optimally cover a given confined layer of the ocean. By applying this algorithm at first the mobile underwater sensors adjust their depth to the specified depth. Then, they make a triangular grid across a given area. Afterwards, they randomly move to spread across the given grid. These control laws only rely on local information also they are easily implemented and computationally effective as they use some easy consensus rules. The feature of exchanging information just among neighbouring mobile sensors keeps the information exchange minimum in the whole networks and makes this algorithm practicable option for undersea. The efficiency of the presented control laws is confirmed via mathematical proof and numerical simulations.
Evaluation quality of service for internet of things based on fuzzy logic: a ...nooriasukmaningtyas
The development of the internet of thing (IoT) technology has become a major concern in sustainability of quality of service (SQoS) in terms of efficiency, measurement, and evaluation of services, such as our smart home case study. Based on several ambiguous linguistic and standard criteria, this article deals with quality of service (QoS). We used fuzzy logic to select the most appropriate and efficient services. For this reason, we have introduced a new paradigmatic approach to assess QoS. In this regard, to measure SQoS, linguistic terms were collected for identification of ambiguous criteria. This paper collects the results of other work to compare the traditional assessment methods and techniques in IoT. It has been proven that the comparison that traditional valuation methods and techniques could not effectively deal with these metrics. Therefore, fuzzy logic is a worthy method to provide a good measure of QoS with ambiguous linguistic and criteria. The proposed model addresses with constantly being improved, all the main axes of the QoS for a smart home. The results obtained also indicate that the model with its fuzzy performance importance index (FPII) has efficiently evaluate the multiple services of SQoS.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Smart monitoring system using NodeMCU for maintenance of production machinesnooriasukmaningtyas
Maintenance is an activity that helps to reduce risk, increase productivity, improve quality, and minimize production costs. The necessity for maintenance actions will increase efficiency and enhance the safety and quality of products and processes. On getting these conditions, it is necessary to implement a monitoring system used to observe machines' conditions from time to time, especially the machine parts that often experience problems. This paper presents a low-cost intelligent monitoring system using NodeMCU to continuously monitor machine conditions and provide warnings in the case of machine failure. Not only does it provide alerts, but this monitoring system also generates historical data on machine conditions to the Google Cloud (Google Sheet), includes which machines were down, downtime, issues occurred, repairs made, and technician handling. The results obtained are machine operators do not need to lose a relatively long time to call the technician. Likewise, the technicians assisted in carrying out machine maintenance activities and online reports so that errors that often occur due to human error do not happen again. The system succeeded in reducing the technician-calling time and maintenance workreporting time up to 50%. The availability of online and real-time maintenance historical data will support further maintenance strategy.
Design and simulation of a software defined networkingenabled smart switch, f...nooriasukmaningtyas
Using sustainable energy is the future of our planet earth, this became not only economically efficient but also a necessity for the preservation of life on earth. Because of such necessity, smart grids became a very important issue to be researched. Many literatures discussed this topic and with the development of internet of things (IoT) and smart sensors, smart grids are developed even further. On the other hand, software defined networking is a technology that separates the control plane from the data plan of the network. It centralizes the management and the orchestration of the network tasks by using a network controller. The network controller is the heart of the SDN-enabled network, and it can control other networking devices using software defined networking (SDN) protocols such as OpenFlow. A smart switching mechanism called (SDN-smgrid-sw) for the smart grid will be modeled and controlled using SDN. We modeled the environment that interact with the sensors, for the sun and the wind elements. The Algorithm is modeled and programmed for smart efficient power sharing that is managed centrally and monitored using SDN controller. Also, all if the smart grid elements (power sources) are connected to the IP network using IoT protocols.
Efficient wireless power transmission to remote the sensor in restenosis coro...nooriasukmaningtyas
In this study, the researchers have proposed an alternative technique for designing an asymmetric 4 coil-resonance coupling module based on the series-to-parallel topology at 27 MHz industrial scientific medical (ISM) band to avoid the tissue damage, for the constant monitoring of the in-stent restenosis coronary artery. This design consisted of 2 components, i.e., the external part that included 3 planar coils that were placed outside the body and an internal helical coil (stent) that was implanted into the coronary artery in the human tissue. This technique considered the output power and the transfer efficiency of the overall system, coil geometry like the number of coils per turn, and coil size. The results indicated that this design showed an 82% efficiency in the air if the transmission distance was maintained as 20 mm, which allowed the wireless power supply system to monitor the pressure within the coronary artery when the implanted load resistance was 400 Ω.
Grid reactive voltage regulation and cost optimization for electric vehicle p...nooriasukmaningtyas
Expecting large electric vehicle (EV) usage in the future due to environmental issues, state subsidies, and incentives, the impact of EV charging on the power grid is required to be closely analyzed and studied for power quality, stability, and planning of infrastructure. When a large number of energy storage batteries are connected to the grid as a capacitive load the power factor of the power grid is inevitably reduced, causing power losses and voltage instability. In this work large-scale 18K EV charging model is implemented on IEEE 33 network. Optimization methods are described to search for the location of nodes that are affected most due to EV charging in terms of power losses and voltage instability of the network. Followed by optimized reactive power injection magnitude and time duration of reactive power at the identified nodes. It is shown that power losses are reduced and voltage stability is improved in the grid, which also complements the reduction in EV charging cost. The result will be useful for EV charging stations infrastructure planning, grid stabilization, and reducing EV charging costs.
Topology network effects for double synchronized switch harvesting circuit on...nooriasukmaningtyas
Energy extraction takes place using several different technologies, depending on the type of energy and how it is used. The objective of this paper is to study topology influence for a smart network based on piezoelectric materials using the double synchronized switch harvesting (DSSH). In this work, has been presented network topology for circuit DSSH (DSSH Standard, Independent DSSH, DSSH in parallel, mono DSSH, and DSSH in series). Using simulation-based on a structure with embedded piezoelectric system harvesters, then compare different topology of circuit DSSH for knowledge is how to connect the circuit DSSH together and how to implement accurately this circuit strategy for maximizing the total output power. The network topology DSSH extracted power a technique allows again up to in terms of maximal power output compared with network topology standard extracted at the resonant frequency. The simulation results show that by using the same input parameters the maximum efficiency for topology DSSH in parallel produces 120% more energy than topology DSSH-series. In addition, the energy harvesting by mono-DSSH is more than DSSH-series by 650% and it has exceeded DSSHind by 240%.
Improving the design of super-lift Luo converter using hybrid switching capac...nooriasukmaningtyas
In this article, an improvement to the positive output super-lift Luo converter (POSLC) has been proposed to get high gain at a low duty cycle. Also, reduce the stress on the switch and diodes, reduce the current through the inductors to reduce loss, and increase efficiency. Using a hybrid switch unit composed of four inductors and two capacitors it is replaced by the main inductor in the elementary circuit. It’s charged in parallel with the same input voltage and discharged in series. The output voltage is increased according to the number of components. The gain equation is modeled. The boundary condition between continuous conduction mode (CCM) and discontinuous conduction mode (DCM) has been derived. Passive components are designed to get high output voltage (8 times at D=0.5) and low ripple about (0.004). The circuit is simulated and analyzed using MATLAB/Simulink. Maximum power point tracker (MPPT) controls the converter to provide the most interest from solar energy.
Third harmonic current minimization using third harmonic blocking transformernooriasukmaningtyas
Zero sequence blocking transformers (ZSBTs) are used to suppress third harmonic currents in 3-phase systems. Three-phase systems where singlephase loading is present, there is every chance that the load is not balanced. If there is zero-sequence current due to unequal load current, then the ZSBT will impose high impedance and the supply voltage at the load end will be varied which is not desired. This paper presents Third harmonic blocking transformer (THBT) which suppresses only higher harmonic zero sequences. The constructional features using all windings in single-core and construction using three single-phase transformers explained. The paper discusses the constructional features, full details of circuit usage, design considerations, and simulation results for different supply and load conditions. A comparison of THBT with ZSBT is made with simulation results by considering four different cases
Power quality improvement of distribution systems asymmetry caused by power d...nooriasukmaningtyas
With an increase of non-linear load in today’s electrical power systems, the rate of power quality drops and the voltage source and frequency deteriorate if not properly compensated with an appropriate device. Filters are most common techniques that employed to overcome this problem and improving power quality. In this paper an improved optimization technique of filter applies to the power system is based on a particle swarm optimization with using artificial neural network technique applied to the unified power flow quality conditioner (PSO-ANN UPQC). Design particle swarm optimization and artificial neural network together result in a very high performance of flexible AC transmission lines (FACTs) controller and it implements to the system to compensate all types of power quality disturbances. This technique is very powerful for minimization of total harmonic distortion of source voltages and currents as a limit permitted by IEEE-519. The work creates a power system model in MATLAB/Simulink program to investigate our proposed optimization technique for improving control circuit of filters. The work also has measured all power quality disturbances of the electrical arc furnace of steel factory and suggests this technique of filter to improve the power quality.
Studies enhancement of transient stability by single machine infinite bus sys...nooriasukmaningtyas
Maintaining network synchronization is important to customer service. Low fluctuations cause voltage instability, non-synchronization in the power system or the problems in the electrical system disturbances, harmonics current and voltages inflation and contraction voltage. Proper tunning of the parameters of stabilizer is prime for validation of stabilizer. To overcome instability issues and get reinforcement found a lot of the techniques are developed to overcome instability problems and improve performance of power system. Genetic algorithm was applied to optimize parameters and suppress oscillation. The simulation of the robust composite capacitance system of an infinite single-machine bus was studied using MATLAB was used for optimization purpose. The critical time is an indication of the maximum possible time during which the error can pass in the system to obtain stability through the simulation. The effectiveness improvement has been shown in the system
Renewable energy based dynamic tariff system for domestic load managementnooriasukmaningtyas
To deal with the present power-scenario, this paper proposes a model of an advanced energy management system, which tries to achieve peak clipping, peak to average ratio reduction and cost reduction based on effective utilization of distributed generations. This helps to manage conventional loads based on flexible tariff system. The main contribution of this work is the development of three-part dynamic tariff system on the basis of time of utilizing power, available renewable energy sources (RES) and consumers’ load profile. This incorporates consumers’ choice to suitably select for either consuming power from conventional energy sources and/or renewable energy sources during peak or off-peak hours. To validate the efficiency of the proposed model we have comparatively evaluated the model performance with existing optimization techniques using genetic algorithm and particle swarm optimization. A new optimization technique, hybrid greedy particle swarm optimization has been proposed which is based on the two aforementioned techniques. It is found that the proposed model is superior with the improved tariff scheme when subjected to load management and consumers’ financial benefit. This work leads to maintain a healthy relationship between the utility sectors and the consumers, thereby making the existing grid more reliable, robust, flexible yet cost effective.
Energy harvesting maximization by integration of distributed generation based...nooriasukmaningtyas
The purpose of distributed generation systems (DGS) is to enhance the distribution system (DS) performance to be better known with its benefits in the power sector as installing distributed generation (DG) units into the DS can introduce economic, environmental and technical benefits. Those benefits can be obtained if the DG units' site and size is properly determined. The aim of this paper is studying and reviewing the effect of connecting DG units in the DS on transmission efficiency, reactive power loss and voltage deviation in addition to the economical point of view and considering the interest and inflation rate. Whale optimization algorithm (WOA) is introduced to find the best solution to the distributed generation penetration problem in the DS. The result of WOA is compared with the genetic algorithm (GA), particle swarm optimization (PSO), and grey wolf optimizer (GWO). The proposed solutions methodologies have been tested using MATLAB software on IEEE 33 standard bus system
Intelligent fault diagnosis for power distribution systemcomparative studiesnooriasukmaningtyas
Short circuit is one of the most popular types of permanent fault in power distribution system. Thus, fast and accuracy diagnosis of short circuit failure is very important so that the power system works more effectively. In this paper, a newly enhanced support vector machine (SVM) classifier has been investigated to identify ten short-circuit fault types, including single line-toground faults (XG, YG, ZG), line-to-line faults (XY, XZ, YZ), double lineto-ground faults (XYG, XZG, YZG) and three-line faults (XYZ). The performance of this enhanced SVM model has been improved by using three different versions of particle swarm optimization (PSO), namely: classical PSO (C-PSO), time varying acceleration coefficients PSO (T-PSO) and constriction factor PSO (K-PSO). Further, utilizing pseudo-random binary sequence (PRBS)-based time domain reflectometry (TDR) method allows to obtain a reliable dataset for SVM classifier. The experimental results performed on a two-branch distribution line show the most optimal variant of PSO for short fault diagnosis.
A deep learning approach based on stochastic gradient descent and least absol...nooriasukmaningtyas
More than eighty-five to ninety percentage of the diabetic patients are affected with diabetic retinopathy (DR) which is an eye disorder that leads to blindness. The computational techniques can support to detect the DR by using the retinal images. However, it is hard to measure the DR with the raw retinal image. This paper proposes an effective method for identification of DR from the retinal images. In this research work, initially the Weiner filter is used for preprocessing the raw retinal image. Then the preprocessed image is segmented using fuzzy c-mean technique. Then from the segmented image, the features are extracted using grey level co-occurrence matrix (GLCM). After extracting the fundus image, the feature selection is performed stochastic gradient descent, and least absolute shrinkage and selection operator (LASSO) for accurate identification during the classification process. Then the inception v3-convolutional neural network (IV3-CNN) model is used in the classification process to classify the image as DR image or non-DR image. By applying the proposed method, the classification performance of IV3-CNN model in identifying DR is studied. Using the proposed method, the DR is identified with the accuracy of about 95%, and the processed retinal image is identified as mild DR.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Slantlet transform used for faults diagnosis in robot arm
1. Indonesian Journal of Electrical Engineering and Computer Science
Vol. 25, No. 1, January 2022, pp. 281~290
ISSN: 2502-4752, DOI: 10.11591/ijeecs.v25.i1.pp281-290 281
Journal homepage: http://ijeecs.iaescore.com
Slantlet transform used for faults diagnosis in robot arm
Muhamad Azhar Abdilatef Alobaidy1,2
, Jassim Mohammed Abdul-Jabbar1
, Saad Zaghlul Al-khayyt2
1
Department of Computer Engineering, College of Engineering, University of Mosul, Mosul, Iraq
2
Department of Mechatronics Engineering, College of Engineering, University of Mosul, Mosul, Iraq
Article Info ABSTRACT
Article history:
Received Aug 20, 2021
Revised Oct 24, 2021
Accepted Nov 25, 2021
The robot arm systems are the most target systems in the fields of faults
detection and diagnosis which are electrical and the mechanical systems in
many fields. Fault detection and diagnosis study is presented for two robot
arms. The disturbance due to the faults at robot's joints causes oscillations at
the tip of the robot arm. The acceleration in multi-direction is analysed to
extract the features of the faults. Simulations for planar and space robots are
presented. Two types of feature (faults) detection methods are used in this
paper. The first one is the discrete wavelet transform, which is applied in
many research's works before. The second type, is the Slantlet transform,
which represents an improved model of the discrete wavelet transform. The
multi-layer perceptron artificial neural network is used for the purpose of
faults allocation and classification. According to the obtained results, the
Slantlet transform with the multi-layer perceptron artificial neural network
appear to possess best performance (4.7088e-05), lower consuming time
(71.017308 sec) and higher accuracy (100%) than the results obtained when
applying discrete wavelet transform and artificial neural network for the
same purpose.
Keywords:
Accuracy
DWT
Faults diagnosis
LabVolt
MLP-ANN
Planer
SLT
This is an open access article under the CC BY-SA license.
Corresponding Author:
Muhamad Azhar Abdilatef Alobaidy
Department of Mechatronics Engineering, Colege of Engineering
University of Mosul, Mosul, Iraq
Email: muhamad.azhar@umosul.edu.iq
1. INTRODUCTION
Robots that being developed in recent years and are now utilized in number of fields. They have
been used in industries, militaries, medical equipment, and many other fields [1]. For most of these
applications, it is recommended that the used robot must be safe and precise as much as possible. That
because any failure in a robot can have a significant impact on the performance during work, resulting in
poor results [1]–[4]. Condition monitoring for robots differs from that simple rotating gear due to their
extremely sophisticated mechanics. To fulfil any given scenario for a robot, each joint in the robot's body will
move at different angular speeds (and accelerations), demand different torques, and rotate at different angles.
The mechanical or electrical impulses sent by the robot will be transitory, lasting only a few seconds. The
signals generated by malfunctioning parts are non-stationary [5]. The fault diagnosis method normally
consists of three steps: fault identification, which may indicate the presence of irregular behaviours, fault
isolation, which determines the location and form of the failure that occurs, and finally fault analysis, which
reveals the relationship between failure causes and symptoms [6], [7]
In 2011, Eski et al. [8] published a study that described an experimental investigation on a robot
manipulator by using a neural network to analyse the vibration condition on joints. Each joint's noise and
vibration were calculated. Then, to predict the servicing time, the relevant parameters are checked with a
neural network predictor. Two types of neural predictors are used to find a stable and adaptive neural
2. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 1, January 2022: 281-290
282
network structure. These two methods enhanced performance, allowing for the adoption of a rotated binary
neural network (RBNN) form to forecast vibrations on industrial robots. In 2016, Jaber and Bicker [9]
developed an intelligent condition monitoring system for industrial robot joints to detect the most common
bearing failures, such as inner/outer race bearing faults. For precise defect diagnosis, the discrete wavelet
transform (DWT) was utilized to perform time-frequency signal analysis. After that, an artificial neural
network (ANN) was applied to classify the faults. Using the PUMA 560 robot, an experimental investigation
setup was carried out. The standard deviation features were computed for multi-band frequency levels and
used to design, train, and test the proposed neural network. The created approach was extremely accurate in
diagnosing a variety of seeded robot defects. Lin and Boldbaatar [10] proposed a model-based fault
accommodation control technique for biped robot locomotion with unknown uncertainties and faults, which
relied on a recurrent wavelet elman neural network (RWENN) to achieve appropriate control with minimal
output degradation. The adaptive laws of the RWENN-based fault accommodation regulation are derived
using the Lyapunov theorem, ensuring the system's stability; a numerical comparison with other neural-
network-based control methods was utilized to illustrate its superiority. In 2019 Cho et al. [11], presented a
method of fault detection using a special algorithm using neural network for robot manipulators. The study
proposes a neural network-based fault detection approach that does not require the use of a physical robot
model or acceleration. A neural network can be used to calculate the fault torque, allowing for successful
defect identification and diagnosis.
According to the obtained results in the pre-mentioned studies, there is no single simulation study
applying more than one technique for the purpose of faults detection and diagnosis. Due to that, no
comparisons have been done between different techniques. Moreover, in the mentioned studies, only one
type of fault in one location at a time is tested; there are no expectations for more types of faults on different
locations. The pre-mentioned studies also give no focus on the consuming time. In addition, the Slantlet
transform (SLT) [12]–[15], is not used yet for the faults diagnosis in robot arms. In this paper, two types of
features (faults) detection methods are used for many faults in many locations at a time, the used methods are
the DWT and the SLT. In the following sections, the robot arm simulation, DWT, SLT, and also the faults
classification are explained deeply; also the results and discussion, conclusion and future works are included.
2. ROBOT ARM SIMULATION
A robot is a reprogrammable multifunctional manipulator that is programmed to move (materials,
components, and tools). The robot arm system can be exposed to many problems, which can lead to failures
or system faults [16]. Robots can malfunction due to human mistake, control panel issues, mechanical faults,
power outages, and environmental variables. The main reason for preventing such failures is that they might
result in human injury or death, as well as costly downtime. Positional error is responsible for half of all
robot failures [17]. The motion of any robot arm is usually depends on the number of joints and their
properties. Thus, there is a difference between the two and the three joints robot arms. Additional z
dimension, which comes from the third joint is added, makes the robot arm's motion more flexible, but with
some complexity in design, works and robot arm's kinematics equations. In this paper, two robot arms are
presented using Matlab Simulink, to simulate real models. The first model is designed to simulate the planar
robot arm (two joints robot arm), Figure 1. The second model is designed to simulate LabVolt 5150 robot
arm Figure 2 and Figure 3.
Figure 1. Two joints robot arm simulation model (planer robot arm)
3. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Slantlet transform used for faults diagnosis in robot arm (Muhamad Azhar Abdilatef Alobaidy)
283
Figure 2. LabVolt 5150 robot arm
Figure 3. LabVolt robot arm simulation
In the two simulations, a cubic trajectory generation block Figure 4 is used representing the typical
implementation case. A standard scope is connected to track the output signal. The original signals in the
joints represent the joints positions. The suitable cubic polynomial has the form [18]:
𝜃(𝑡) = 𝜃0 + (3/𝑡𝑓2)(𝜃𝑓 − 𝜃0)𝑡2
− (2/𝑡𝑓3
)(𝜃𝑓 − 𝜃0)𝑡3
(1)
where;
𝜃0:initial position
𝜃𝑓:final position
𝑡𝑓:time duration for motion
The signals are then merged with an external signal as a disturbance model, which consists of a
repeated stair sequence with a gain. The purpose of using the disturbance model is to used the robot signals
faulty. The signal at each joint of the robot arm is to be converted into Cartesian coordinates using the
forward kinematics equations. The forward kinematics equations for the planner are:
𝑋 = 𝐿1𝐶𝑂𝑆𝜃 + 𝐿2𝐶𝑂𝑆(𝜃1 + 𝜃2) (2)
𝑌 = 𝐿1𝑆𝐼𝑁 𝜃 + 𝐿2𝑆𝐼𝑁 (𝜃1 + 𝜃2) (3)
While, the forward kinematics for LabVolt 5 robot arm are:
𝑋 = 𝐶𝑂𝑆𝜃1[𝐿1𝐶𝑂𝑆𝜃2 + 𝐿2𝐶𝑂𝑆(𝜃1 + 𝜃2)] (4)
𝑌 = 𝐿1𝑆𝐼𝑁 𝜃2 + 𝐿2𝑆𝐼𝑁 (𝜃2 + 𝜃3) (5)
𝑍 = 𝑆𝐼𝑁𝜃1[𝐿1𝐶𝑂𝑆𝜃2 + 𝐿2𝐶𝑂𝑆(𝜃2 + 𝜃3)] (6)
Where; L1 and L2 are the lengths of link1 and link 2; respectively.
4. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 1, January 2022: 281-290
284
For noisy or faulty signals, it is preferred to deal with the acceleration signals (the 2nd
order
derivation of positions) because they are more sensitive to both time- and frequency-changes. In this paper,
the detected acceleration signals are to be registered and diagnosed with the wavelet transform, and the
process is repeated with SLT. ANN is then used to classify the defective signals. The most detected faulty
signals occur because of the unstable torque or force applied to the joints or because of high loads, which
lead to additional noisy signals, appear as oscillations [17], [19]. The acceleration is expected to be easily
read since accelerometer sensors are used in the majority of real-world recent works [4]. A noisy signal is
produced in this simulation by adding a disturbance signal at joints. This condition causes the original signals
to be disrupted, resulting in the output of a defective signal. The ANN is then applied for the purpose of
fault's classification.
3. DISCRETE WAVELET TRANSFORM
The wavelet is considered as one of the recent approaches for signal transformation, that has a wide
range of applications [20]. The wavelet transform is viewed as a solution to the shortest time fourier
transform (STFT)'s problems. As shown in Figure 4, it considers a variety of windows with varying scales
and widths (7). In this way, the wavelet transform will divide data into several frequency components and
investigate each one separately [16], [20].
Figure 4. Wavelet time-scale representation [16]
𝛹/𝑎, 𝑏(𝑡) =
1
√𝑎
𝛹(
𝑡−𝑏
𝑎
) (7)
The wavelet transform is used to decompose non-stationary time series domains into frequency–
time domains in a variety of fields [21]. This concept's mean is a little wave, which is an oscillatory function
for a zero average that is localized in a minor span. Wavelet coefficients can be manipulated in a frequency-
based manner, then, inverted to a time-based representation. The mother wavelet function can be modified to
generate other daughter wavelet functions, forming the wavelet family group. Each daughter wavelet
function is a moved-extended, or a moved-compressed version of the mother wavelet [21]. The wavelet
transform is divided into two types: continuous and discrete. Haar and Daubechies are usual forms of discrete
wavelet that are discontinues in time, possessing Shannon discontinues in frequency [22]. According to the
applications' purposes, discrete wavelet transforms is used. The impracticality and redundancy of continues
wavelet transform (CWT) are both familiar problems; the first is because both parameters are constant, while
the second is due to the wavelet's existence. During the wavelet calculation, when the continuously-scalable
function is continuously shifted the over the signal to determine the correlation between them, the stated
redundancy problem occurs. As a result, the wavelet coefficients must be extremely redundant [23]. The
DWT is a type of wavelet that is developed by sampling the wavelet coefficients to overcome this problem.
The discrete wavelet is not continuously scalable or translatable, but it can be scaled and translated in discrete
steps. To accomplish this, the wavelet equation is modified as shown in (8).
𝛹𝑗′𝑘(𝑡)=
1
√𝑆0
𝐽
𝛹 (
𝑡−𝑘Ʈ0 𝑆0
𝐽
𝑆0
𝐽 ) (8)
5. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Slantlet transform used for faults diagnosis in robot arm (Muhamad Azhar Abdilatef Alobaidy)
285
Where;(j, k) are integers, and (s0>1) is a constant dilation phase. The dilation phase determines the
translation factor S0 in (8). S0 is usually set to two such that the frequency axis sampling leads to dyadic
sampling. The translation factor is normally set to one; this results in a dyadic sampling of the time axis.S=2j
,
t=k*2j
. In this paper, Daubechies four (DB4), which is a type of DWT, is used for the purpose of fault
detection in robot arm signals (trajectory). This type is proposed to be used because of the limited period of
time used to complete the trajectory (path) of the used simulated robot arm. Five levels are analyzed to reach
the suitable banks' filters for the purpose of features extraction. Figure 5, D0-D4 represent the features for
faults diagnosis, the high frequencies, which represent the high pass filters' (HPFs) outputs, are depended.
While the low frequencies from the low pass filters (LPFs) are not used.
Figure 5. Wavelet five level opened diagram
4. SLANTLET TRANSFORM
The DWT is a teqniche used especially for multi-resolution analytic applications. It has changeable
windows that are short at high frequencies and long at low frequencies [24]. To solve one of DWT's
weaknesses, the inability to construct an ideal discrete time basis for a finite number of zero moments,
Selesnick invented the SLT in 1999, a type of filter comparable to DWT that outperforms DWT by
increasing time localization qualities [12]. SLT is a high-resolution multi-resolution approach that uses
piecewise linear data. SLT, is like DWT, in orthogonality and capability of decomposition at several
resolutions. SLT filters are commonly implemented as a tree structure with filter bank iteration, whereas
DWT filters are typically built as a tree structure without filter bank iteration [25], [26]. SLT is just a series
of parallel filters built from an orthogonal DWT with a time-localization improvement [24], as shown in
Figure 6. In [27], the second scale's coefficients of SLT filter bank were calculated with their. Sum-of-
powers-of-two (SOPOT) representations, while the third scale coefficients of SLT filter bank were calculated
in (9) and (10) [28]. In such work, the same coefficients for second scales were obtained. Those coefficients
of the SLT filters' bank (F2(z), G2(z), and z-3
G1(1/z) are used in this paper for the purpose of feature detection
(fault diagnosis), while H2(z) filter which represents the LPF is not used, because of its inefficient
coefficients. These measured and used coefficients were relied on and used. The coefficients of the used
filters are convoluted with the robot arm's output acceleration signals of each joint to extract the required
features for fault diagnosis. These diagnosed features are then used as inputs for an ANN to identify the
faults according to their types and locations. The coefficients of the 2nd
scale SLT's filter bank are shown in
Tables 1-4.
gi(x) = {
a0′0 + a1′0 for n = 0 … . 2j
a1′0 + a1′1 ∗ (n − 2j) for n = 2j
… 2j+1
− 1
m=2j
S1= 6* √(m)/((m^2 ) − 1) (4m^2 − 1))
t1=2* √3/(m(m2 − 1)
S0= -S1 * (m − 1)/ (9)
t0 =((m+1)(s1/3)-mt1)((m-1)/2m)
a0′0 = (s0 + t0)/2
a1′0 = (s0 − t0)/2
a0′1 = (s1 + t1)/2
a1′1 = (s1 − t1)/2 (10)
6. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 1, January 2022: 281-290
286
Figure 6. Second scale SLT filter bank structure
Table 1. SLT second scale H2(z) filter's initial coefficients
SLT Filters h(0) h(1) h(2) h(3) h(4) h(5) h(6) h(7)
Coefficients 0.2698 0.3948 0.5198 0.6448 0.2302 0.1052 −0.0198 −0.1448
Table 2. SLT second scale F2 (z) filter's initial coefficients
SLT Filters h(0) h(1) h(2) h(3) h(4) h(5) h(6) h(7)
Coefficients −0.0825 −0.1207 −0.1589 −0.1971 0.7533 0.3443 −0.0648 −0.4738
Table 3. SLT second scale Initial coefficients of G1(𝒛) filter
SLT Filter h(0) h(1) h(2) h(3)
Coefficients −0.5117 0.8279 −0.1208 −0.1954
Table 4. SLT second scale initial coefficients of G1(𝒛) filter (𝒁−
(𝟏/𝒛))
SLT Filter h(0) h(1) h(2) h(3)
Coefficients −0.1954 −0.1208 0.8279 −0.5117
5. FAULTS CLASSIFICATION
The mostly used process for the purpose of separation and classification in recent studies, is the
ANN. Jaber [4], [5] the multi- layer perceptron (MLP) with one hidden layer is used, refereeing to that and
according to their accurate results obtained beside of its similarity of this works, the same ANN with some
modifications, is used here. In this work, two simulations are designed and tested, the first one is a planer
robot arm that has two joints, while the second simulation is also a robot arm but with three joints. The faults
are supposed to be happened in joints, each joint can be exposed to problems, which usually lead to faults,
causing a motion's failure in robot. Ten inputs/four outputs MLP is designed for the planer robot arm, and
fifteen inputs/eight outputs is designed for the LabVolt (three joints example) robot arm manipulator,
Table 5. The data is divided according to that 70% for training, 15% for validation and 15% for testing
process. The confusion matrix, which is calculated to show the adjacency between the output and targets in
addition to the system accuracy.
Table 5. MLP-ANN characteristics
Characteristics Planner robot arm LabVolt robot arm
1 Number of input layer neurons 10 15
2 Number of hidden layer neurons 1 1
3 Number of output layer neurons 4 8
5 Hidden layer activation function Bayesian Regularization Bayesian Regularization
6 Output layer activation function Linear Linear
7 Learning rate 0,05 0,05
8 Minimum performance gradient 1.00e-07 1.00e-07
9 Maximum number of epoch 5000 5000
6. RESULTS AND DESCUTION
In this section, a faults diagnosis study is presented; two methods of fault detection and diagnosis
(DWT and SLT) are applied for the acceleration output signals of two robot arm simulations (Planer and
7. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Slantlet transform used for faults diagnosis in robot arm (Muhamad Azhar Abdilatef Alobaidy)
287
LabVolt), Figure 7. Both of robot arm models are built using Matlab Simulink. As mentioned before,
disturbance signal is added to the joints of the robot arms joints. Many cases are supposed to be happened; in
the planer simulation four cases are expected to be happened according to the following scenario:
One of the two joints are disturbed (two cases)
Both of the joints disturbed (one case)
Both of the joints are healthy (one case)
In the second designed simulation, which represent LabVolt industrial robot arm (three joints robot
arm), eight cases can be expected to be happened when disturbance signals have to be added according to the
following scenario:
One joint disturbed signal (three cases)
Two joints are disturbed (three cases)
All signals' joints are healthy (one case)
All signals' joints are disturbed (one case)
Each of these cases, for the both simulations, is referred to a motion situation which represents
signals of acceleration in (x, y) directions for the planner, and in (x, y, z) directions for the LabVolt robot
arm. These cases can indicate if the motion is noisy (distorted signal) or not, specifying the location of
disturbance if exists. The recorded initial and final positions for planer are [-15o
, 15o
] and [60o
, 75o
];
respectively, while for LabVolt robot arm are [-15o
, -15o
, 15o
] and [60o
, 60o
, 75o
]; respectively. At the
beginning, the robot arm simulation is run, for a duration time, the acceleration signals are recorded using
0.001 sec. as a simulation time per wall clock and 3.973 sec. for all [1], [5]. Each recorded signal consists of
(3973) samples in a raw, representing the three-directions accelerations (Ax, Ay, Az). After the completion
of data recording, the features detection process is taken a place. A five-level decomposition with DB4 filters
is applied for the data, it gave better and stable results with more accuracy than others (DWT with less than
five number of level decomposition). Thus by using wavelet for the planer robot arm (x, and y), ten output
coefficients are resulted, while fifteen coefficients are produced for the LabVolt robot arm simulation (x, y,
and z). Each of the resulting wavelet coefficient consists of (1x1990) samples. As mentioned before, four
cases are expected to be happened due to the faults with their locations. According to that, each one of the ten
coefficients (D0–D10), will be produced four times (four cases). These coefficients are then concatenated as
shown in Figure 7. After concatenation, ten inputs of 1x7960 samples (4x1990) will be applied as an input to
the ANN for the purpose of faults classification according to their locations. The MLP is used for this
purpose (as in section 5, Table 5). The same procedure is repeated for the LabVolt robot arm simulation, but
with three signals in the (x, y, and z) directions. The results of these experiments are recorded in Table 6.
Figure 7. Planner robot arm's faults diagnosis process
As shown in Figure 7, four outputs from the ANN will represent four classes. when the inputs to the
ANN are related to data in case 1, then the ANN output will be [1 0 0 0], while when they are related to cases
two, thee and four, ANN output will be [0 1 0 0], [0 0 1 0], and [0 0 0 1] respectively as given in Table 6. The
same procedure is used for the LabVolt (three joints) robot arm simulation, but with differences of fifteen
8. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 1, January 2022: 281-290
288
inputs and eight classes (ANN outputs), Table 7. As mentioned in section 5, the MLP-ANN is used for the
purpose of features (faults) classification. The Bayesian regularization activation function is used for the
hidden layer that has 18 neurons (the best-experimented case), and the linear activation function is used for
the output layer. The accuracy of the system reaches 93.9% for the planner robot arm, while it reaches 88.6%
for the LabVolt robot arm using DWT.
Table 6. MLP-ANN classification for planar cases
Cases Output Fault location
1 [1 0 0 0] No faults (Healthy)
2 [0 1 0 0] Joint 1 (Shoulder)
3 [0 0 1 0] Joint 2 (Arm)7
4 [0 0 0 1] Joint 1 & 2
Table 7. MLP-ANN classification LabVolt cases
Cases Output Fault location
1 [1 0 0 0 0 0 0 0] No faults (Healthy)
2 [0 1 0 0 0 0 0 0] Joint 1 (Base)
3 [0 0 1 0 0 0 0 0] Joint 2 (Shoulder)
4 [0 0 0 1 0 0 0 0] Joints 1 & 2
5 [0 0 0 0 1 0 0 0] Joint 3 (Arm)
6 [0 0 0 0 0 1 0 0] Joint 1 & 3
7 [0 0 0 0 0 0 1 0] Joints 2 & 3
8 [0 0 0 0 0 0 0 1] Joints 1, 2, & 3
The results of these experiments are recorded in Table 8. In the second part, the SLT filters (F2(z),
𝑮𝟏(𝒛), and (𝒁−𝟑𝑮𝟏(𝟏/𝒛)) are used instead of the DWT for the purpose of feature (faults) detection. The
acceleration's signals those comes from coordinates (x, and y) in planar and (x, y and z) in LabVolt are
convoluted with the coefficients of these banks filters of the SLT [25]. The resulted features are used as
inputs for the MLP-ANN to classify the faults according to their types and locations. The accuracy by using
these filters instead of the DWT is increased to be 100% for the planar and 99.9% for the LabVolt robot arm,
Table 9.
Table 8. DWT (5 level Db4) and ANN for faults' diagnosis in robot arms
Robot arm Performance (MSE) Time of Process (sec) Accuracy
1 Planar 0.0259 3075.551457 93.9%
2 LabVolt 0.0282 16369.924428 88.6%
Table 9. SLT 2 scale and ANN for faults' diagnosis in robot arms
Robot arm Performance (MSE) Time of Process(sec) Accuracy
1 Planar 4.7088e-05 71.017308 100%
2 LabVolt 8.3969e-05 26.460 99.9%
According to the given results in Tables 8 and 9, it is clear to proof that the SLT filters are much
better than the DWT for the faults' diagnosis in robot arms, for both planar and three joints robot arms.
Besides the accuracy, the processing time needed for the SLT is smaller than the time needed for the DWT,
also the number of iterations is reduced for reaching the results with better performance.
7. CONCLUSION
Nowadays, faults diagnosis is a very important field to focus on and perform many studies about.
The signal of robot arm tip's accelerations always give the required information about faults. The DWT was
used in many works for the purpose of faults diagnosis in a robot arm, but only for one joint. In this paper
many faulty joints have been studied at the same time. Two methods have been used; namely, the DWT and
the SLT filters. The features of the faults at joints have been extracted clearly from coefficients of the two
methods. More than one fault at the same time in different joints have been detected and isolated in the
simulation. The suggested methods have succeeded in detecting and isolating the faults in robot arm joints
9. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Slantlet transform used for faults diagnosis in robot arm (Muhamad Azhar Abdilatef Alobaidy)
289
which are moving in short time duration tasks. The results of SLT have shown better accuracy, smaller time
of process, better performance, and lesser complexity than the DWT. Thus, the method of using both (SLT
and MLP-ANN) is suggested to be used instead of (DWT and MLP-ANN) for fault diagnosis, especially in
robotics systems.
ACKNOWLEDGEMENTS
The authors would like to express their gratitude to the faculty and staff of the University of Mosul's
College of Engineering, especially the departments of computer engineering and mechatronics engineering,
for their contributions to this research.
REFERENCES
[1] M. H. Terra and R. Tinós, “Fault detection and isolation in robotic manipulators via neural networks: A comparison among three
architectures for residual analysis,” Journal of Robotic Systems, vol. 18, no. 7, pp. 357–374, 2001, doi: 10.1002/rob.1029.
[2] J. Halme, “Condition monitoring of a material handling industrial robot,” in Condition Monitoring and Diagnostic Engineering
Management: COMADEM 2006, Luleå University of Technology, pp. 415–424, 2006.
[3] D. Baleanu, “Wavelet Transform and Some of Its Real-World Applications,” BoD–Books, 2015, doi: 10.5772/59743.
[4] A. A. Jaber, "Design of an intelligent embedded system for condition monitoring of an industrial robot,". Springer 2016.
[5] A. A. Jaber and R. Bicker, “Industrial robot fault detection based on wavelet transform and LabVIEW,” in IEEE First
International Conference on Systems Informatics, Modelling and Simulation, Sheffield, United Kingdom, 2014, pp. 21–31, doi:
10.1109/SIMS.20014.27.
[6] S. Hara, Y. Kawahara, T. Washio, P. von Bünau, T. Tokunaga, and K. Yumoto, “Separation of stationary and non-stationary
sources with a generalized eigenvalue problem,” Neural Networks, vol. 33, pp. 7–20, 2012, doi: 10.1016/j.neunet.2012.04.001.
[7] L. M. Capisani, A. Ferrara, A. F. de Loza, and L. M. Fridman, “Manipulator Fault Diagnosis via Higher Order Sliding-Mode
Observers,” IEEE Transactions on Industrial Electronics, vol. 59, no. 10, pp. 3979–3986, 2012, doi: 10.1109/tie.2012.2189534.
[8] I. Eski, S. Erkaya, S. Savas, and S. Yildirim, “Fault detection on robot manipulators using artificial neural networks,” Robotics and
Computer-Integrated Manufacturing, vol. 27, no. 1, pp. 115–123, 2011, doi: 10.1016/j.rcim.2010.06.017.
[9] A. A. Jaber and R. Bicker, “Industrial robot backlash fault diagnosis based on discrete wavelet transform and artificial neural
network,” American Journal of Mechanical Engineering, vol. 4, no. 1, pp. 21–31, 2016, doi: 10.12691/ajme-4-1-4.
[10] C.-M. Lin and E.-A. Boldbaatar, “Fault Accommodation Control for a Biped Robot Using a Recurrent Wavelet Elman Neural
Network,” IEEE Systems Journal, vol. 11, no. 4, pp. 2882–2893, 2017, doi: 10.1109/jsyst.2015.2409888.
[11] C. N. Cho, J. T. Hong, and H. J. Kim, “Neural Network Based Adaptive Actuator Fault Detection Algorithm for Robot
Manipulators,” Journal of Intelligent & Robotic Systems, vol. 95, no. 1, pp. 137–147, Jul. 2019, doi: 10.1007/s10846-018-0781-0.
[12] I. W. Selesnick, “The slantlet transform,” IEEE Transactions on Signal Processing, vol. 47, no. 5, pp. 1304–1313, 1999, doi:
10.1109/78.757218.
[13] G. Panda and S. K. Meher, “An Efficient Approach to Signal Compression using Slantlet Transform,” IETE Journal of Research,
vol. 46, no. 5, pp. 299–307, 2000, doi: 10.1080/03772063.2000.11416169.
[14] R. T. Mohammed and B. E. Khoo, “Image watermarking using slantlet transform,” 2012 IEEE Symposium on Industrial
Electronics and Applications. IEEE, 2012, doi: 10.1109/isiea.2012.6496644.
[15] M. Maitra and A. Chatterjee, “A Slantlet transform based intelligent system for magnetic resonance brain image classification,”
Biomedical Signal Processing and Control, vol. 1, no. 4, pp. 299–306, 2006, doi: 10.1016/j.bspc.2006.12.001.
[16] M. A. Alobaidy, D. J. Abdul-Jabbar, and S. Al-khayyt, “Faults Diagnosis in Robot Systems: A Review,” Al-Rafidain Engineering
Journal (AREJ), vol. 25, no. 2, pp. 166–177, 2020, doi: 10.33899/rengj.2020.127782.1051.
[17] S. Z. S. Al-Khayyt, “Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking,” Al-Khwarizmi
Engineering Journal, vol. 9, no. 1, pp. 19-28, 2013.
[18] P. Zhao, Y. Zhou, and R. Zhou, “A New Trajectory Optimizing Method Using Input Shaping Principles,” Shock and Vibration,
vol. 2018, pp. 1–11, 2018, doi: 10.1155/2018/4173253.
[19] Y. Gao and R. J. Patton, “Application of wavelet analysis for performance monitoring and diagnosis of a hydraulic pump,” IFAC
Proceedings Volumes, vol. 36, no. 5, pp. 333–338, 2003, doi: 10.1016/s1474-6670(17)36513-8.
[20] M. Rhif, A. Ben Abbes, I. Farah, B. Martínez, and Y. Sang, “Wavelet Transform Application for/in Non-Stationary Time-Series
Analysis: A Review,” Applied Sciences, vol. 9, no. 7, p. 1345, 2019, doi: 10.3390/app9071345.
[21] A. Asuncion, “Signal Processing Applications of Wavelets, Information and Computer Science,” University of California, Irvine,
2002.
[22] A. N. Akansu and E. Al, "Multiresolution signal decomposition: transforms, subbands, and wavelets,". Academic press, 2001.
[23] E. Khalastchi and M. Kalech, “On Fault Detection and Diagnosis in Robotic Systems,” ACM Computing Surveys, vol. 51, no. 1,
pp. 1–24, 2018, doi: 10.1145/3146389.
[24] M. I. Gursoy, A. S. Yilmaz, and S. V. Ustun, “A practical real-time power quality event monitoring applications using discrete
wavelet transform and artificial neural network,” Journal of Engineering Science and Technology, vol. 13, no. 6, pp. 1764–1781,
2018.
[25] G. Panda, P. K. Dash, A. K. Pradhan, and S. K. Meher, “Data compression of power quality events using the slantlet transform,”
IEEE Transactions on Power Delivery, vol. 17, no. 2, pp. 662–667, 2002, doi: 10.1109/61.997957.
[26] T. Z. Ismaeel, “Design & Evaluation of a Steganography System for Speech Signal by Slantlet Transform,” Diyala Journal of
Engineering Sciences, vol. 5, no. 2, pp. 99–113, 2012.
[27] A. M. Jasim, H. M. Abd, and J. M. Abdul-Jabbar, “Complexity reduction of slantlet transform structure based on the multiplierless
realization,” Journal of Engineering Science and Technology, vol. 15, no. 3, pp. 1705–1718, 2020.
[28] H. N. Abdullah and S. A. Ali, “Implementation of 8-point Slantlet transform based polynomial cancellation coding-OFDM system
using FPGA,” 2010 7th International Multi- Conference on Systems, Signals and Devices. IEEE, 2010, doi:
10.1109/ssd.2010.5585601.
10. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 1, January 2022: 281-290
290
BIOGRAPHIES OF AUTHORS
Muhamad Azhar Abdilatef Alobaidy received the B.Sc. degree in Computer
Engineering from University of Mosul, Mosul, Iraq, in 2006, M.Sc. degree from Cankaya
University, Turkey. Ph.D. candidate in Computer engineering Department, College of
Engineering, University of Mosul. He is a lecturer at Mechatronics Engineering Department,
University of Mosul. He was the head of Scientific affairs department at the presidency of the
University of Mosul. Currently, he is the head of culture relationships division, University of
Mosul. He has many published papers. He is a reviewer at edas. He can be contacted at email:
muhamad.azhar@uomosul.edu.iq.
Jassim Mohammed Abdul-Jabbar received the B.Sc. and M.Sc. degrees in
Elictrical engineering from al Basra University Basra, Iraq. Ph.D. degree in Electrical
engineering from Baghdad University, Baghdad, Iraq. He has been a professor of Digital
Signal Processing in engineering. He was the Head of Electrical Engineering Department,
College of Engineering, University of Basra, Basra, Iraq. He was the Head of Computer
Engineering Department, College of Engineering, University of Mosul, Mosul, Iraq. He has
many published papers. He can be contacted at email: drjssm@uomosul.edu.iq.
Saad Zaghlul Al-khayyt received the B.Sc. and M.Sc. degrees in Mechanical
engineering from Al-Nahreen University, in 1992, and 1995 respectly, Baghdad, Iraq, and the
Ph.D. degree in Mechanical engineering from Russia. He has been an assistant professor of
Mechatronics engineering in 2010. He is currently the Head of Mechatronis Engineering
Department, College of Engineering, University of Mosul. He has many published papers. He
can be contacted at email: Saeeds70@uomosul.edu.iq.