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.
Mems Based Motor Fault Detection in Windmill Using Neural NetworksIJRES Journal
Today wind turbine technology is one of the fastest growing power generation technologies operating in large numbers at harsh and difficult environment sites and it is difficult to monitor each and every windmill separately. There are times when faults occur in motors of windmills are not detected in earlier stage and we come to know about damage when motor gets fully damaged. Here we using wireless monitoring based on MEMS accelerometer sensor which senses the vibrations occurring in the motor and based on the severity of vibrations, sensor sends the data to the controlling unit to take further action. Neural network based work is included to get the accurate and precise vibratory signals to detect fault at a very early stage to avoid full damage to the motor.
Fault detection and diagnosis of high speed switching devices in power invertereSAT Journals
Abstract
Power electronic based inverters are the major components in industry. A fault diagnostics framework composed of a pattern recognition system, having machine learning technology as its integral part is utilized for failure detection of different switches and tracing multiple types of faults in an inverter. Hardware point of view power electronics inverter can be considered to be the weakest link. Hence, this work is carried on detecting faults and classifies which switches in the inverter cause the fault. Diagnosis can help to avoid unplanned breakdown, to make possible to run an emergency operation in case of a fault. On the basis of theoretical foundations of electronic power inverter a simulation model has been developed to simulate the healthy condition and all single-switch open circuit faults. The generated signal is processed using Discrete Wavelet Transform (DWT) and Fuzzy Inference Logic (FIL). A smart and accurate classification of faults is obtained using simulation results, which are tested on a wide operation domain and various load conditions.
Keywords: Fault Diagnosis, DWT, Fuzzy Logic, Artificial Intelligence (AI).
A first response microcontroller basedIJCI JOURNAL
This paper presents the microcontroller based advanced technique to design and development of a portable
radiation survey meter to measure low level gamma radiation using NAI(T1) scintillation detector. A
scintillation detector was used as radiation detector and a microcontroller PIC16F876 was used to control
the function of the developed system. The microcontroller generated square wave frequency at specified
pulse width to produce high voltage (+1200V) and regulates it. The high voltage was required to activate
the scintillation detector. Preamplifier and amplifier were designed to make the detector signal for the
further amplification. Microcontroller senses the pulses from the amplifier output and processes data by
software and displays the results. The microcontroller was programmed using a high level programming
language ‘C’ with PCWH compiler.
Mems Based Motor Fault Detection in Windmill Using Neural NetworksIJRES Journal
Today wind turbine technology is one of the fastest growing power generation technologies operating in large numbers at harsh and difficult environment sites and it is difficult to monitor each and every windmill separately. There are times when faults occur in motors of windmills are not detected in earlier stage and we come to know about damage when motor gets fully damaged. Here we using wireless monitoring based on MEMS accelerometer sensor which senses the vibrations occurring in the motor and based on the severity of vibrations, sensor sends the data to the controlling unit to take further action. Neural network based work is included to get the accurate and precise vibratory signals to detect fault at a very early stage to avoid full damage to the motor.
Fault detection and diagnosis of high speed switching devices in power invertereSAT Journals
Abstract
Power electronic based inverters are the major components in industry. A fault diagnostics framework composed of a pattern recognition system, having machine learning technology as its integral part is utilized for failure detection of different switches and tracing multiple types of faults in an inverter. Hardware point of view power electronics inverter can be considered to be the weakest link. Hence, this work is carried on detecting faults and classifies which switches in the inverter cause the fault. Diagnosis can help to avoid unplanned breakdown, to make possible to run an emergency operation in case of a fault. On the basis of theoretical foundations of electronic power inverter a simulation model has been developed to simulate the healthy condition and all single-switch open circuit faults. The generated signal is processed using Discrete Wavelet Transform (DWT) and Fuzzy Inference Logic (FIL). A smart and accurate classification of faults is obtained using simulation results, which are tested on a wide operation domain and various load conditions.
Keywords: Fault Diagnosis, DWT, Fuzzy Logic, Artificial Intelligence (AI).
A first response microcontroller basedIJCI JOURNAL
This paper presents the microcontroller based advanced technique to design and development of a portable
radiation survey meter to measure low level gamma radiation using NAI(T1) scintillation detector. A
scintillation detector was used as radiation detector and a microcontroller PIC16F876 was used to control
the function of the developed system. The microcontroller generated square wave frequency at specified
pulse width to produce high voltage (+1200V) and regulates it. The high voltage was required to activate
the scintillation detector. Preamplifier and amplifier were designed to make the detector signal for the
further amplification. Microcontroller senses the pulses from the amplifier output and processes data by
software and displays the results. The microcontroller was programmed using a high level programming
language ‘C’ with PCWH compiler.
Calculating voltage magnitudes and voltage phase angles of real electrical ne...IJECEIAES
In the field of electrical network, it is necessary, under different conditions, to learn about the behavior of the system. Power Flow Analysis is the tool per excellent that allow as to make a deep study and define all quantities of each bus of the system. To determine power flow analysis there is a lot of methods, we have either numerical or intelligent techniques. Lately, researchers always work on finding intelligent methods that allow them to solve their complex problems. The goal of this article is to compare two intelligent methods that are capable of predicting quantities; artificial neural network and adaptive neuro-fuzzy inference system using real electrical networks. To do that we used few significant discrepancies. These methods are characterized by giving results in real time. To make this comparison successful, we implemented these two methods, to predict the voltage magnitudes and the voltage phase angles, on two Moroccan electrical networks. The results of the comparison show that the method of adaptive neuro-fuzzy inference system have more advantages than the method of artificial neural network.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Distance relay is mainly used for fault detection in the power system. But it cannot be used below 11kV. Hence an electronic smart energy meter is developed for the detection of the fault in the distribution system. It consists of a fault detection circuit and an IoT module. The fault detector senses the presence of a fault and give a command signal to the circuit breaker and also passes these fault signal to the operator. This proposed system will be a perfect solution for three major challenges faced in the distribution sector such as automatic fault isolation, information about the fault to the operator and exact location of the fault. The energy meter is capable of displaying the cost of the unit consumed according to their tariff. The variation in tariff can be controlled by an operator using IoT. The initial cost of the proposed system is comparatively higher than the traditional system. As a long term consideration, the cost of installation can be compensated by reducing the wastage of energy by making the consumer aware of the consumption details.
Wireless Fault Detection System for an Industrial Robot Based on Statistical ...IJECEIAES
Industrial robots are now commonly used in production systems to improve productivity, quality and safety in manufacturing processes. Recent developments involve using robots cooperatively with production line operatives. Regardless of application, there are significant implications for operator safety in the event of a robot malfunction or failure, and the consequent downtime has a significant impact on productivity in manufacturing. Machine healthy monitoring is a type of maintenance inspection technique by which an operational asset is monitored and the data obtained is analysed to detect signs of degradation and thus reducing the maintenance costs. Developments in electronics and computing have opened new horizons in the area of condition monitoring. The aim of using wireless electronic systems is to allow data analysis to be carried out locally at field level and transmitting the results wirelessly to the base station, which as a result will help to overcome the need for wiring and provides an easy and cost-effective sensing technique to detect faults in machines. So, the main focuses of this research is to develop an online and wireless fault detection system for an industrial robot based on statistical control chart approach. An experimental investigation was accomplished using the PUMA 560 robot and vibration signal capturing was adopted, as it responds immediately to manifest itself if any change is appeared in the monitored machine, to extract features related to the robot health conditions. The results indicate the successful detection of faults at the early stages using the key extracted parameters.
Solar panel monitoring solution using IoT-Faststream TechnologiesSudipta Maity
Faststream Technologies offers an automated IOT based solar panel monitoring/troubleshooting system that allows for automated solar panel monitoring from anywhere over the internet. As part of our solution, we make use of several IoT gateways suitable for different needs, based on SoCs like STM32, ESP32, ublox, CC3200, SiliconLabs, to monitor the solar panel parameters, in turn, providing Solar Plant Insights.
Our system constantly monitors the solar panel and transmits various parameters to the Cloud over the IoT system. Here we make use of the IoT platform to transmit solar power parameters to Amazon/ Azure cloud /IOT server via the gateway (over WiFi and Ethernet). A powerful web interface allows viewing of data in meaningful formats, enabling users to make decisions.
PERFORMANCE ANALYSIS OF ENERGY EFFICIENT SCALABLE HEIRARCHIAL PROTOCOL FOR HO...IAEME Publication
Wireless Sensor nodes connect the physical world to the digital world using smart,
tiny and self configured stand alone devices. These small devices offer pack of
brilliant opportunities to the digital world by capturing and revealing real time events
which later used as data cloud in numerous applications. With impressive
improvements in protocols, node level programming, simulation platforms and
middleware developments sensor nodes have become promising options in the
development of smart cities, gas and chemical industry, precision agriculture etc.
However, these industrial application demands more lifetime and faster-secure data
transmissions. In many applications it is recorded that with increase in network size
LEACH routing protocol functioning degenerate. Further, designing of a promising
routing protocol that can maintain less energy consumption during data gathering
and propagation leads to use of variety of approaches. This work is based on the
abstraction of equal distribution of energy among nodes with scalability.
Experimental results show commendable improvement in network lifespan with
residual energy of nodes to last for longer period. Throughput is also monitored
considering scalability.
Overall fuzzy logic control strategy of direct driven PMSG wind turbine conne...IJECEIAES
The fuzzy logic strategies reported in the literature about the control of direct drive permanent magnet synchronous generator (PMSG) connected to grid are limited in terms of inclusiveness and efficiency. So an overall control based on fuzzy logic and anti-windup compensation is proposed in this paper. Aiming at the inadequate of hill climb search (HCS) MPPT with fixed step size, the fuzzy logic is introduced in the stage of "generating rotor speed reference" to overcome the oscillations and slowness in traditional method. PI controllers are replaced by anti-windup fuzzy logic controllers in the "machine side control" stage and in "grid side control" stage to pertinently regulate the reference parameters. Then comparison tests with classical methods are implemented under varying climatic conditions. The results obtained demonstrate that the developed control is superior to other methods in response time (less than 4.528E-04 s), precision (an overshoot about 0.41%) and quality of produced energy (efficiency is 91%). The study verifying the feasibility and effectiveness of this algorithm in PMSG wind turbine connected to grid.
AC drives are employed in process industries for varying applications resulting in a wide range of ratings. The entire process industry has seen a paradigm shift from manual to automated systems. The major factor contributing to this is the advanced power electronics technology enabling power electronic drives for smooth control of electric motors. Induction motors are most commonly used in industries. Faults in the power electronic circuits may occur periodically. These faults often go unnoticed as they rarely cause a complete shutdown and the fault levels may not be large enough to lead to a breakdown of the drive. An early detection of these faults is required to prevent their escalation into major faults. The diagnostic tool for detection of faults requires real time monitoring of the entire drive. In this work, detailed investigation of different faults that can occur in the power electronic circuit of an industrial drive is carried out. Analysis and impact of faults on the performance of the induction motor is presented. A real time monitoring platform is proposed to detect and classify the fault accurately using machine learning. A diagnostic tool also is developed to display the severity and location of the fault to the operator to take corrective measures.
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.
Calculating voltage magnitudes and voltage phase angles of real electrical ne...IJECEIAES
In the field of electrical network, it is necessary, under different conditions, to learn about the behavior of the system. Power Flow Analysis is the tool per excellent that allow as to make a deep study and define all quantities of each bus of the system. To determine power flow analysis there is a lot of methods, we have either numerical or intelligent techniques. Lately, researchers always work on finding intelligent methods that allow them to solve their complex problems. The goal of this article is to compare two intelligent methods that are capable of predicting quantities; artificial neural network and adaptive neuro-fuzzy inference system using real electrical networks. To do that we used few significant discrepancies. These methods are characterized by giving results in real time. To make this comparison successful, we implemented these two methods, to predict the voltage magnitudes and the voltage phase angles, on two Moroccan electrical networks. The results of the comparison show that the method of adaptive neuro-fuzzy inference system have more advantages than the method of artificial neural network.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Distance relay is mainly used for fault detection in the power system. But it cannot be used below 11kV. Hence an electronic smart energy meter is developed for the detection of the fault in the distribution system. It consists of a fault detection circuit and an IoT module. The fault detector senses the presence of a fault and give a command signal to the circuit breaker and also passes these fault signal to the operator. This proposed system will be a perfect solution for three major challenges faced in the distribution sector such as automatic fault isolation, information about the fault to the operator and exact location of the fault. The energy meter is capable of displaying the cost of the unit consumed according to their tariff. The variation in tariff can be controlled by an operator using IoT. The initial cost of the proposed system is comparatively higher than the traditional system. As a long term consideration, the cost of installation can be compensated by reducing the wastage of energy by making the consumer aware of the consumption details.
Wireless Fault Detection System for an Industrial Robot Based on Statistical ...IJECEIAES
Industrial robots are now commonly used in production systems to improve productivity, quality and safety in manufacturing processes. Recent developments involve using robots cooperatively with production line operatives. Regardless of application, there are significant implications for operator safety in the event of a robot malfunction or failure, and the consequent downtime has a significant impact on productivity in manufacturing. Machine healthy monitoring is a type of maintenance inspection technique by which an operational asset is monitored and the data obtained is analysed to detect signs of degradation and thus reducing the maintenance costs. Developments in electronics and computing have opened new horizons in the area of condition monitoring. The aim of using wireless electronic systems is to allow data analysis to be carried out locally at field level and transmitting the results wirelessly to the base station, which as a result will help to overcome the need for wiring and provides an easy and cost-effective sensing technique to detect faults in machines. So, the main focuses of this research is to develop an online and wireless fault detection system for an industrial robot based on statistical control chart approach. An experimental investigation was accomplished using the PUMA 560 robot and vibration signal capturing was adopted, as it responds immediately to manifest itself if any change is appeared in the monitored machine, to extract features related to the robot health conditions. The results indicate the successful detection of faults at the early stages using the key extracted parameters.
Solar panel monitoring solution using IoT-Faststream TechnologiesSudipta Maity
Faststream Technologies offers an automated IOT based solar panel monitoring/troubleshooting system that allows for automated solar panel monitoring from anywhere over the internet. As part of our solution, we make use of several IoT gateways suitable for different needs, based on SoCs like STM32, ESP32, ublox, CC3200, SiliconLabs, to monitor the solar panel parameters, in turn, providing Solar Plant Insights.
Our system constantly monitors the solar panel and transmits various parameters to the Cloud over the IoT system. Here we make use of the IoT platform to transmit solar power parameters to Amazon/ Azure cloud /IOT server via the gateway (over WiFi and Ethernet). A powerful web interface allows viewing of data in meaningful formats, enabling users to make decisions.
PERFORMANCE ANALYSIS OF ENERGY EFFICIENT SCALABLE HEIRARCHIAL PROTOCOL FOR HO...IAEME Publication
Wireless Sensor nodes connect the physical world to the digital world using smart,
tiny and self configured stand alone devices. These small devices offer pack of
brilliant opportunities to the digital world by capturing and revealing real time events
which later used as data cloud in numerous applications. With impressive
improvements in protocols, node level programming, simulation platforms and
middleware developments sensor nodes have become promising options in the
development of smart cities, gas and chemical industry, precision agriculture etc.
However, these industrial application demands more lifetime and faster-secure data
transmissions. In many applications it is recorded that with increase in network size
LEACH routing protocol functioning degenerate. Further, designing of a promising
routing protocol that can maintain less energy consumption during data gathering
and propagation leads to use of variety of approaches. This work is based on the
abstraction of equal distribution of energy among nodes with scalability.
Experimental results show commendable improvement in network lifespan with
residual energy of nodes to last for longer period. Throughput is also monitored
considering scalability.
Overall fuzzy logic control strategy of direct driven PMSG wind turbine conne...IJECEIAES
The fuzzy logic strategies reported in the literature about the control of direct drive permanent magnet synchronous generator (PMSG) connected to grid are limited in terms of inclusiveness and efficiency. So an overall control based on fuzzy logic and anti-windup compensation is proposed in this paper. Aiming at the inadequate of hill climb search (HCS) MPPT with fixed step size, the fuzzy logic is introduced in the stage of "generating rotor speed reference" to overcome the oscillations and slowness in traditional method. PI controllers are replaced by anti-windup fuzzy logic controllers in the "machine side control" stage and in "grid side control" stage to pertinently regulate the reference parameters. Then comparison tests with classical methods are implemented under varying climatic conditions. The results obtained demonstrate that the developed control is superior to other methods in response time (less than 4.528E-04 s), precision (an overshoot about 0.41%) and quality of produced energy (efficiency is 91%). The study verifying the feasibility and effectiveness of this algorithm in PMSG wind turbine connected to grid.
Similar to Sensor Fault Detection and Isolation Based on Artificial Neural Networks and Fuzzy Logic Applicated on Induction Motor for Electrical Vehicle
AC drives are employed in process industries for varying applications resulting in a wide range of ratings. The entire process industry has seen a paradigm shift from manual to automated systems. The major factor contributing to this is the advanced power electronics technology enabling power electronic drives for smooth control of electric motors. Induction motors are most commonly used in industries. Faults in the power electronic circuits may occur periodically. These faults often go unnoticed as they rarely cause a complete shutdown and the fault levels may not be large enough to lead to a breakdown of the drive. An early detection of these faults is required to prevent their escalation into major faults. The diagnostic tool for detection of faults requires real time monitoring of the entire drive. In this work, detailed investigation of different faults that can occur in the power electronic circuit of an industrial drive is carried out. Analysis and impact of faults on the performance of the induction motor is presented. A real time monitoring platform is proposed to detect and classify the fault accurately using machine learning. A diagnostic tool also is developed to display the severity and location of the fault to the operator to take corrective measures.
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.
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.
FUZZY LOGIC APPROACH FOR FAULT DIAGNOSIS OF THREE PHASE TRANSMISSION LINEJournal For Research
Transmission line among the other electrical power system component suffers from unexpected failure due to various random causes. Because transmission line is quite large as it is open in environment. A fault occurs on transmission line when two or more conductors come in contact with each other or ground. This paper presents a proposed model based on MATLAB software to detect the fault on transmission line. Fault detection has been achieved by using Fuzzy Logic based intelligent control technique. The proposed method aims in presenting a fast and accurate fault diagnosis method to classify and identify the type of fault which occurs on a power transmission system. In this paper, some of the unconventional approaches for condition monitoring of power systems comprising of relay Breaker, along with the application of soft computing technique like fuzzy logic. Results show that the proposed methodology is efficient in identifying fault in transmission system.
Automatic Fault Detection System with IOT BasedYogeshIJTSRD
The fault location is an important part for any transmission line and distribution system. The location of fault is difficult task sometimes it takes lot of times needed for the exact location of the fault. The exact fault location can help the service man to overcome the fault free system in very less time. In this paper we are able to detect the fault range in easy way using the ESP module and the message is transferred on the mobile. This project is cost effective and reliable. Fast fault detection provide the protection of equipment before any significant damage. Er. Sanjeev Kumar | Mohd Mehraj Khan | Nadeem | Shailesh Kumar Yadav | Harsh Gupta "Automatic Fault Detection System with IOT Based" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43806.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/43806/automatic-fault-detection-system-with-iot-based/er-sanjeev-kumar
Design of Data Aquistion interface circuit used in Detection Inter-turn Fault...IJERA Editor
A commitment to condition monitoring involves the operators of plant in the conduct of a range of activities. These activities may be complicated in nature and indeed may often be performed automatically under computer control. They can, however, always be down into a relatively small number of easily identifiable functional tasks. This makes it much easier to identify the common elements of machine condition monitoring schemes .The Motor Current Signature Analysis (MCSA) is considered the most popular fault detection method now a day because it can easily detect the common machine fault such as turn to turn short circuit . The present paper discusses the fundamentals of Motor Current Signature Analysis (MCSA) plus condition monitoring of the induction motor using MCSA. A proposed interface circuit design and application will be further explain in this paper, the implemented monitoring unit circuit also illustrated, see appendix A. Artificial neural networks are extensively used for speed, torque estimation, and solid state drive control in both DC and AC machines. Two scenarios presented in this paper, first ten turns assume to be shorted, and in the second thirty turns shorted to show the difference in the amplitude of frequencies at each case. Finally artificial intelligent techniques are increasingly used for condition monitoring and fault detection of machines. This paper present. An improvement in three-phase squirrel-cage induction motor stator inter-turn fault detection and diagnosis based on a neural network approach is presented.
Principal component analysis based approach for fault diagnosis in pneumatic ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
GSM Based Transformer Fault Monitoring Systemijtsrd
Transformer is a important part of the transmission and distribution system. Transformers Monitoring for problems before they occurs can prevent the faults that are expensive to repair and results in loss of service. Transformers are the essential part of power transmission network and expensive, as the cost of power failures. Because of much cost of scheduled and unscheduled maintenance, especially at the remote sites, the utility industry began investing in instrumentation and monitoring of the transformer. in this project we are implementing and of a mobile embedded system to monitor key parameters of a distribution transformer like load currents, oil level and ambient temperature. The idea of monitoring system integrates a global service mobile Modem, with a single chip microcontroller and different sensor interfacing. It is installed at the distribution transformer site and the above parameters are recorded using the analog to digital converter ADC of the embedded system. The parameters are processed and recorded in the system memory. If any emergency situation occurs the system sends SMS message to the mobile phones containing information about abnormality according to some predefined instructions which are programmed in the microcontroller. This system mobile will help the transformers to operate perfectly and identify problems before any failure. Assi. Prof. T. S. Barhate | Mr. Mangesh Patil | Mr. Vaibhav Bhagat | Mr. Rahul Ugale | Mr. Shubham Kandelkar | Mr. Kiran Tikare "GSM Based Transformer Fault Monitoring System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-4 , June 2022, URL: https://www.ijtsrd.com/papers/ijtsrd50166.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/50166/gsm-based-transformer-fault-monitoring-system/assi-prof-t-s-barhate
This paper focuses on the materials, working principle of a robotic vehicle which will be controlled with hand motion. The aim of this research is to enhance industrialization by creating a hand motion controlled robotic vehicle, since it uses hand motion it will be easier to use in automation and various industries. It is also very beneficial for people with disabilities since only hand motion is required. There were various materials that were used in the research. 2 microcontrollers, an accelerometer, RF modules, encoder, decoder, diode, motor driver IC, DC motor and batteries. The microcontrollers are small computers which can be programmed to be utilized in various different ways. The Accelerometer is a PCB or a sensor which detects speed. The RF modules are of two types which are transmitters and receivers and they are components which are used to send data and information wirelessly. The encoder and decoder are used to convert the binary to any n number of output terminals. The diode is used to send the electricity in one direction. The motor driver IC controls the DC motor from the information given by the microcontroller ICs and lastly a 9v Battery will be used to power the system. The arduino software will be used to program the IC so it can perform the required task. The gadget features a receiver circuit that is intended to be worn on top of the user's glove. The vehicle's circuit incorporates an RF receiver, an 8051 CPU, and a Driver IC to power the motors. This method is extremely useful for persons with impairments since it allows a robotic vehicle to drive itself using hand gestures. The person only needs to move his hand to move the car forward, backward, left, or right. As a result, the user is not required to push any buttons.
Actuator Fault Decoupled Residual Generation on Lateral Moving AircraftTELKOMNIKA JOURNAL
Implementation of time-scheduled maintenance is not suitable if it is applied for systems with
many varieties of heavy workload and harsh environment since on that condition components degrade
earlier that those under normal condition. Therefore it has been shifted to condition-based maintenance
(CBM). One important aspect, among others, toward implementation of CBM method is fault isolation. The
problem investigated in this paper is related todecouple residual generation for actuator fault isolation of an
aircraft on lateral movement. The proposed solution for that problem is to implement combination of
transformation matrix and special filter. Transformation matrix is used to convert feature locations of
actuator faults to signature vectors. Moreover, the signature vectors will be processed further by special
filter to generate decoupled residuals. It is assumed that the actuator is the only fault when the aircraft is
on lateral movement. The result showed that special filter and transformation matrix can be designed so
that the residual of aileron actuator fault is decoupled from the residual of rudder actuator fault.
Design and Implementation of Speed Control of Induction Motor using Arduino B...ijtsrd
The low maintenance and robustness induction motors have many applications in the industries. The speed control of induction motor is more important to achieve maximum torque and efficiency. Various speed control techniques like, Direct Torque Control, Sensorless Vector Control and Field Oriented Control. Soft computing technique – the Fuzzy logic is applied in this work .We have carried on with the hardware implementation for speed control of induction motor using the fuzzy logic control . Using the arduino micro controller, we have developed a hardware setup which is able to control the speed of induction motor by using Arduino Uno .We can conclude that we have been able to get a good control over the speed of motor. Talat Jabeen | Ganesh Wakte ""Design and Implementation of Speed Control of Induction Motor using Arduino Based FLC"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23684.pdf
Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/23684/design-and-implementation-of-speed-control-of-induction-motor-using-arduino-based-flc/talat-jabeen
Similar to Sensor Fault Detection and Isolation Based on Artificial Neural Networks and Fuzzy Logic Applicated on Induction Motor for Electrical Vehicle (20)
The aim of this research is the speed tracking of the permanent magnet synchronous motor (PMSM) using an intelligent Neural-Network based adapative backstepping control. First, the model of PMSM in the Park synchronous frame is derived. Then, the PMSM speed regulation is investigated using the classical method utilizing the field oriented control theory. Thereafter, a robust nonlinear controller employing an adaptive backstepping strategy is investigated in order to achieve a good performance tracking objective under motor parameters changing and external load torque application. In the final step, a neural network estimator is integrated with the adaptive controller to estimate the motor parameters values and the load disturbance value for enhancing the effectiveness of the adaptive backstepping controller. The robsutness of the presented control algorithm is demonstrated using simulation tests. The obtained results clearly demonstrate that the presented NN-adaptive control algorithm can provide good trackingperformances for the speed trackingin the presence of motor parameter variation and load application.
This paper presents a fast and accurate fault detection, classification and direction discrimination algorithm of transmission lines using one-dimensional convolutional neural networks (1D-CNNs) that have ingrained adaptive model to avoid the feature extraction difficulties and fault classification into one learning algorithm. A proposed algorithm is directly usable with raw data and this deletes the need of a discrete feature extraction method resulting in more effective protective system. The proposed approach based on the three-phase voltages and currents signals of one end at the relay location in the transmission line system are taken as input to the proposed 1D-CNN algorithm. A 132kV power transmission line is simulated by Matlab simulink to prepare the training and testing data for the proposed 1D- CNN algorithm. The testing accuracy of the proposed algorithm is compared with other two conventional methods which are neural network and fuzzy neural network. The results of test explain that the new proposed detection system is efficient and fast for classifying and direction discrimination of fault in transmission line with high accuracy as compared with other conventional methods under various conditions of faults.
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
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.
This paper focuses on the artificial bee colony (ABC) algorithm, which is a nonlinear optimization problem. is proposed to find the optimal power flow (OPF). To solve this problem, we will apply the ABC algorithm to a power system incorporating wind power. The proposed approach is applied on a standard IEEE-30 system with wind farms located on different buses and with different penetration levels to show the impact of wind farms on the system in order to obtain the optimal settings of control variables of the OPF problem. Based on technical results obtained, the ABC algorithm is shown to achieve a lower cost and losses than the other methods applied, while incorporating wind power into the system, high performance would be gained.
The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP) . The azimuth angle of the sun is evaluated using GPS which provide latitude, date, longitude and time. The image processing used to find sun image through which centroid of sun is calculated and finally by comparing the centroid of sun with GPS quadrate to achieve optimum tracking point. Weather conditions and situation observed through AI decision making with the help of IP algorithms. The presented advance adaptation is analyzed and established via experimental effects which might be made available on the memory of the cloud carrier for systematization. The proposed system improve power gain by 59.21% and 10.32% compare to stable system (SS) and two-axis solar following system (TASF) respectively. The reduced tracking error of IoT based Two-axis solar following system (IoT-TASF) reduces their azimuth angle error by 0.20 degree.
Kosovo has limited renewable energy resources and its power generation sector is based on fossil fuels. Such a situation emphasizes the importance of active research and efficient use of renewable energy potential. According to the analysis of meteorological data for Kosovo, it can be concluded that among the most attractive potential wind power sites are the locations known as Kitka (42° 29' 41" N and 21° 36' 45" E) and Koznica (42° 39′ 32″ N, 21° 22′30″E). The two terrains in which the analysis was carried out are mountain areas, with altitudes of 1142 m (Kitka) and 1230 m (Koznica). the same measuring height, about 84 m above the ground, is obtained for these average wind speeds: Kitka 6,667 m/s and Koznica 6,16 m/s. Since the difference in wind speed is quite large versus a difference in altitude that is not being very large, analyses are made regarding the terrain characteristics including the terrain relief features. In this paper it will be studied how much the roughness of the terrain influences the output energy. Also, that the assumption to be taken the same as to how much they will affect the annual energy produced.
Large-scale grid-tied photovoltaic (PV) station are increasing rapidly. However, this large penetration of PV system creates frequency fluctuation in the grid due to the intermittency of solar irradiance. Therefore, in this paper, a robust droop control mechanism of the battery energy storage system (BESS) is developed in order to damp the frequency fluctuation of the multi-machine grid system due to variable active power injected from the PV panel. The proposed droop control strategy incorporates frequency error signal and dead-band for effective minimization of frequency fluctuation. The BESS system is used to consume/inject an effective amount of active power based upon the frequency oscillation of the grid system. The simulation analysis is carried out using PSCAD/EMTDC software to prove the effectiveness of the proposed droop control-based BESS system. The simulation result implies that the proposed scheme can efficiently curtail the frequency oscillation.
This study investigates experimentally the performance of two-dimensional solar tracking systems with reflector using commercial silicon based photovoltaic module, with open and closed loop control systems. Different reflector materials were also investigated. The experiments were performed at the Hashemite University campus in Zarqa at a latitude of 32⁰, in February and March. Photovoltaic output power and performance were analyzed. It was found that the modified photovoltaic module with mirror reflector generated the highest value of power, while the temperature reached a maximum value of 53 ̊ C. The modified module suggested in this study produced 5% more PV power than the two-dimensional solar tracking systems without reflector and produced 12.5% more PV power than the fixed PV module with 26⁰ tilt angle.
This paper focuses on the modeling and control of a wind energy conversion chain using a permanent magnet synchronous machine. This system behaves a turbine, a generator, DC/DC and DC/AC power converters. These are connected on both sides to the DC bus, where the inverter is followed by a filter which is connected to the grid. In this paper, we have been used two types of controllers. For the stator side converter, we consider the Takagi-Sugeno approach where the parameters of controller have been computed by the theory of linear matrix inequalities. The stability synthesis has been checked using the Lyapunov theory. According to the grid side converter, the proportional integral controller is exploited to keep a constant voltage on the DC bus and control both types of powers. The simulation results demonstrate the robustness of the approach used.
The development of modeling wind speed plays a very important in helping to obtain the actual wind speed data for the benefit of the power plant planning in the future. The wind speed in this paper is obtained from a PCE-FWS 20 type measuring instrument with a duration of 30 minutes which is accumulated into monthly data for one year (2019). Despite the many wind speed modeling that has been done by researchers. Modeling wind speeds proposed in this study were obtained from the modified Rayleigh distribution. In this study, the Rayleigh scale factor (Cr) and modified Rayleigh scale factor (Cm) were calculated. The observed wind speed is compared with the predicted wind characteristics. The data fit test used correlation coefficient (R2), root means square error (RMSE), and mean absolute percentage error (MAPE). The results of the proposed modified Rayleigh model provide very good results for users.
This paper deals with an advanced design for a pump powered by solar energyto supply agricultural lands with water and also the maximum power point is used to extract the maximum value of the energy available inside the solar panels and comparing between techniques MPPT such as Incremental conductance, perturb & observe, fractional short current circuit, and fractional open voltage circuit to find the best technique among these. The solar system is designed with main parts: photovoltaic (PV) panel, direct current/direct current (DC/DC) converter, inverter, filter, and in addition, the battery is used to save energy in the event that there is an increased demand for energy and not to provide solar radiation, as well as saving energy in the case of generation more than demand. This work was done using the matrix laboratory (MATLAB) simulink program.
The objective of this paper is to provide an overview of the current state of renewable energy resources in Bangladesh, as well as to examine various forms of renewable energies in order to gain a comprehensive understanding of how to address Bangladesh's power crisis issues in a sustainable manner. Electricity is currently the most useful kind of energy in Bangladesh. It has a substantial influence on a country's socioeconomic standing and living standards. Maintaining a stable source of energy at a cost that is affordable to everyone has been a constant battle for decades. Bangladesh is blessed with a wealth of natural resources. Bangladesh has a huge opportunity to accelerate its economic development while increasing energy access, livelihoods, and health for millions of people in a sustainable way due to the renewable energy system.
When the irradiance distribution over the photovoltaic panels is uniform, the pursuit of the maximum power point is not reached, which has allowed several researchers to use traditional MPPT techniques to solve this problem Among these techniques a PSO algorithm is used to have the maximum global power point (GMPPT) under partial shading. On the other hand, this one is not reliable vis-à-vis the pursuit of the MPPT. Therefore, in this paper we have treated another technique based on a new modified PSO algorithm so that the power can reach its maximum point. The PSO algorithm is based on the heuristic method which guarantees not only the obtaining of MPPT but also the simplicity of control and less expensive of the system. The results are obtained using MATLAB show that the proposed modified PSO algorithm performs better than conventional PSO and is robust to different partial shading models.
A stable operation of wind turbines connected to the grid is an essential requirement to ensure the reliability and stability of the power system. To achieve such operational objective, installing static synchronous compensator static synchronous compensator (STATCOM) as a main compensation device guarantees the voltage stability enhancement of the wind farm connected to distribution network at different operating scenarios. STATCOM either supplies or absorbs reactive power in order to ensure the voltage profile within the standard-margins and to avoid turbine tripping, accordingly. This paper present new study that investigates the most suitable-location to install STATCOM in a distribution system connected wind farm to maintain the voltage-levels within the stability margins. For a large-scale squirrel cage induction generator squirrel-cage induction generator (SCIG-based) wind turbine system, the impact of STATCOM installation was tested in different places and voltage-levels in the distribution system. The proposed method effectiveness in enhancing the voltage profile and balancing the reactive power is validated, the results were repeated for different scenarios of expected contingencies. The voltage profile, power flow, and reactive power balance of the distribution system are observed using MATLAB/Simulink software.
The electrical and environmental parameters of polymer solar cells (PSC) provide important information on their performance. In the present article we study the influence of temperature on the voltage-current (I-V) characteristic at different temperatures from 10 °C to 90 °C, and important parameters like bandgap energy Eg, and the energy conversion efficiency η. The one-diode electrical model, normally used for semiconductor cells, has been tested and validated for the polemeral junction. The PSC used in our study are formed by the poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl C61-butyric acid methyl ester (PCBM). Our technique is based on the combination of two steps; the first use the Least Mean Squares (LMS) method while the second use the Newton-Raphson algorithm. The found results are compared to other recently published works, they show that the developed approach is very accurate. This precision is proved by the minimal values of statistical errors (RMSE) and the good agreement between both the experimental data and the I-V simulated curves. The obtained results show a clear and a monotonic dependence of the cell efficiency on the studied parameters.
The inverter is the principal part of the photovoltaic (PV) systems that assures the direct current/alternating current (DC/AC) conversion (PV array is connected directly to an inverter that converts the DC energy produced by the PV array into AC energy that is directly connected to the electric utility). In this paper, we present a simple method for detecting faults that occurred during the operation of the inverter. These types of faults or faults affect the efficiency and cost-effectiveness of the photovoltaic system, especially the inverter, which is the main component responsible for the conversion. Hence, we have shown first the faults obtained in the case of the short circuit. Second, the open circuit failure is studied. The results demonstrate the efficacy of the proposed method. Good monitoring and detection of faults in the inverter can increase the system's reliability and decrease the undesirable faults that appeared in the PV system. The system behavior is tested under variable parameters and conditions using MATLAB/Simulink.
The electrical distribution network is undergoing tremendous modifications with the introduction of distributed generation technologies which have led to an increase in fault current levels in the distribution network. Fault current limiters have been developed as a promising technology to limit fault current levels in power systems. Though, quite a number of fault current limiters have been developed; the most common are the superconducting fault current limiters, solid-state fault current limiters, and saturated core fault current limiters. These fault current limiters present potential fault current limiting solutions in power systems. Nevertheless, they encounter various challenges hindering their deployment and commercialization. This research aimed at designing a bridge-type nonsuperconducting fault current limiter with a novel topology for distribution network applications. The proposed bridge-type nonsuperconducting fault current limiter was designed and simulated using PSCAD/EMTDC. Simulation results showed the effectiveness of the proposed design in fault current limiting, voltage sag compensation during fault conditions, and its ability not to affect the load voltage and current during normal conditions as well as in suppressing the source powers during fault conditions. Simulation results also showed very minimal power loss by the fault current limiter during normal conditions.
This paper provides a new approach to reducing high-order harmonics in 400 Hz inverter using a three-level neutral-point clamped (NPC) converter. A voltage control loop using the harmonic compensation combined with NPC clamping diode control technology. The capacitor voltage imbalance also causes harmonics in the output voltage. For 400 Hz inverter, maintain a balanced voltage between the two input (direct current) (DC) capacitors is difficult because the pulse width modulation (PWM) modulation frequency ratio is low compared to the frequency of the output voltage. A method of determining the current flowing into the capacitor to control the voltage on the two balanced capacitors to ensure fast response reversal is also given in this paper. The combination of a high-harmonic resonator controller and a neutral-point voltage controller working together on the 400 Hz NPC inverter structure is given in this paper.
Direct current (DC) electronic load is a useful equipment for testing the electrical system. It can emulate various load at a high rating. The electronic load requires a power converter to operate and a linear regulator is a common option. Nonetheless, it is hard to control due to the temperature variation. This paper proposed a DC electronic load using the boost converter. The proposed electronic load operates in the continuous current mode and control using the integral controller. The electronic load using the boost converter is compared with the electronic load using the linear regulator. The results show that the boost converter able to operate as an electronic load with an error lower than 0.5% and response time lower than 13 ms.
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Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
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The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Vaccine management system project report documentation..pdfKamal Acharya
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602
and identified using analytical redundancy as presented in the different works [5]-[8]. Unfortunately, the
analytical model could be imprecise and uncertain that‟s why the residual could indicate a false alarm. For
this reason these techniques are well-suited for deterministic models. To solve this problem, intelligent
techniques are used. This category has many advantages: uncertainty, complex and disturbance system
modeling. Therefore, these techniques are required in this problem type, where the detection and the isolation
of the fault for the sensors of specifying system will be guaranteed with desired performances. Many
works have used intelligent techniques to adopt the detection sensor failures for various systems as presented
in [9]-[11]. Authors developed this approach taking advantages on the one hand of digital control
implementation hardware and software specifications and on the other hand, of electrical systems
specifications. The simplicity of the final algorithm leads to low execution time and low consumed resources
for digital implementation.
To successfully implement on the FPGA board the FDI algorithm for the induction motor and
realized an embedded system. There are three methods: the first is to directly program our FPGA using
VHDL, the disadvantage of this method it is that we cannot visualize the behavior of real-time of the control.
The second is to use the toolbox added to Matlab / Simulink HDL coder, the disadvantage of this method that
the toolbox missing a lot and we are obliged to make several approximations and the resulting program is not
optimized. And the last consists to use the toolbox added to Simulink Xilinx System Generator (XSG), the
advantage of this programming method is the resolution of all problems of display. We can also take
advantage of Simulink and visualize the actual behavior of the machine before implementation.
This paper gives detailed information on a new current sensor FDI algorithm, which is developed
using intelligent techniques (Neuro Fuzzy). After this introductory section, the problem statement is
presented, with a description of the machine model and its control system. The architecture of the Neuro
Fuzzy schema used for generation and evaluation is discussed in section 3. Simulation results are given in
section 4 to illustrate the performance of the proposed Neuro-Fuzzy FDI scheme for sensor fault diagnosis of
the induction motor.
2. SYSTEM OVERVIEW
2.1. Presentation
Automotive application drives (EV) has some major requirements that are summarized as
follows [3]-[4]:
1. high torque at low speeds for starting, as well as high power at high speed for cruising;
2. fast torque response;
3. high power density and high instant power;
4. high efficiency for regenerative braking, over wide speed and torque;
5. reasonable cost.
The traction of an electric vehicle can subdivide in three parts: a power source, an inverter and a
receiver (see Figure 1). The source is the battery and the receiver is the mechanical chain. The powertrain
composed of the inverter (and its control) and the motor is the electromechanical power converter.
Faults can affect all the components of the system: induction motor, power converters, connectors
and sensors. The failures in the electric motor can have various origins:
a. Failures related to the exploitation that can lead to faults and also a premature degradation ;
b. Failures related to wrong weak dimensioning and design which lead to a premature degradation
It is very important to detect a sensor failure on a real-time basis for structural health monitoring and
vibration control. Many fault detection and isolation FDI techniques for current sensors have been discussed
over the past decades Frank 1990, Gertler 1991. The two major sensor failure detection methods can be
distinguished:
a. Direct pattern recognition of sensor readings that indicate a fault and an analysis of the discrepancy
between the sensor readings and expected values, derived from some model. In the latter case, it is
typical that a fault is said to be detected if the discrepancy or residual goes above a certain threshold.
b. In signal processing based FDI, some mathematical or statistical operations are performed on the
measurements, or some intelligent technique is trained using measurements to extract the
information about the fault.
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Sensor Fault Detection and Isolation Based on Artificial Neural Networks … (Souha Boukadida)
603
Figure 1. Main components of an EV traction drive.
2.2. Basic Principle of DTC SVM
The conventional DTC strategy is a developed drive control technique of the IM. This type of torque
and flux control was first proposed as direct self-control by Depenbrock [17] and DTC by Takahashi and
Noguchi [18]. The DTC method is characterized by its simple implementation, fast dynamic response, and
robustness to the rotor parameter variation essentially. The main idea of DTC SVM is to recover the
reduction of the ripples of torque and flux, and to have superior dynamic performances. Figure 2 present a
possible schematic of Direct Torque Control by using Space Vector Modulation. There are two different
loops corresponding to the magnitudes of the stator flux and torque. The error between the estimated stator
flux magnitude φs and the reference stator flux magnitude φs
*
is the input of a bloc SVM.
Knowing that in the graduation phase voltages (Va, Vb, Vc) are represented in the plane by a vector
Vs. Each modulation period Tmod of the inverter, the projected vector Vs on the two adjacent vectors assures
the switching time of calculation. The values of these projections provide the desired commutation times.
The key step of the SVM technique is the determination of Ti and Ti+1 during every modulation period Tmod.
To illustrate the methodology we consider the case where Vs can be compounded by the active voltage
vectors V1 and V2.
Figure 2. Bloc diagram of DTC
The stator voltage and stator current are calculated from the state of three phase (Sa ,Sb ,Sc) and
measured currents (ia, ib, ic).
Induction motor
Inverter
Battery
Sa
Sb
Sc
I
M
Voltage source
Inverter
T
φ
T*
s
φ*
s
Ti
Ti+1
Vsα
Vsβ
Flux and torque
estimator
Calculation
Sa, Sb, Sc
PI
PI
Calculation
Ti , Ti+1
α, β
d, q
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2 4
3 3
0
2 4
3 3
2
( , , ) ( )
3
2
( , , ) ( )
3
j j
s a b c a b c
j j
s a b c a b c
V S S S E S S e S e
i i i i i i e i e
Expressing the voltage vector Vs in the graduation (α, β) we have:
1 2
1 2
mod mod
s s s
T T
V V jV V V
T T
Expanding this equation it is possible to express the time T1 and T2 in terms of Vsα and Vsβ. The conduction
time will be expressed as follows:
mod
1
mod
2
3 1
( . ).
2 2
2. .
s s
s
T
T V V
E
T
T V
E
Consequently, the duties expressions are given as follows:
s s
1
s
2
0 1 2
3 V 1 V
.
E E
2 2
V
2
E
1
D
D
D D D
The space vector in sector 1 is shown in figure 3.The time duration of zero vectors is divided equally into
(V0, V1, V2, V7, V2, V1, V0), whereas the time duration of each nonzero vector is distributed into two parts.
This sequence can ensure that is one phase switches when the switching pattern switches, thus can reduce the
harmonic component of the output current and the loss of switching devices. The duties of each phase of the
inverter are presented as follows:
1 2
1 2
1 2
0.5(1 )
0.5(1 )
0.5(1 )
a
b
c
S D D
S D D
S D D
Figure. 3 Sequences of the switches states in sector N1
(1)
(2)
(3)
(4)
(5)
Sc
Sb
Sa
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3. FAULT DETECTION and ISOLATION (FDI)
FDI system is designed as a hybrid system in which fuzzy system and neural networks may
cooperate and interact to implement efficiently the required FDI tasks. The structure of Neuro Fuzzy is
successful applications rely on the ease of rule base design, applicability to complex, uncertain and nonlinear
systems, linguistic modeling, learning abilities, parallel processing. The FDI scheme is divided into two
steps (detection step and localization step). The first step is based on generating a signal called residual. It‟s
used like indictor of the occurrence of the fault. If the difference is equal to zero, then the equipment system
operate in healthy case, otherwise (residual ≠0) they are affected by a fault which should be isolated. The role
of the second step is to determine the time of the default application. In order to get the adequate decision,
this phase requires a technique deals with uncertain data. The most appropriate technique is the Neuro Fuzzy
logic. It needs an expert system. The Figure 4 shows the different stages of the adopted strategy.
Figure 4. Adopted strategy
3.1. Phase Detection
In the case of nonlinear systems, a residue generator by conventional quantitative methods is not an
easy task. It would be better to use neural networks to generate residues functions, using their ability to
model nonlinear functions. Beforehand, a database must be performed offline with expert knowledge. It must
include the main characteristics of the process (operating point, stability, noise ...). In order to make the
neural network describe the behavior of the system, it should be learned with data base rich in information.
Once this base is realized, a structure of the neural network must be chosen.
3.2. Phase of localization
The role of the residual Fuzzification Evaluation step is to identify the element (current sensors)
attached by the fault. In order to get the adequate decision, this phase requires a technique deals with
uncertain data. The most appropriate technique is the fuzzy logic. It needs an expert system. The Figure 5
shows the different stages of the adopted strategy.
An NF generally consists of two principal units: (a) a fuzzifie which converts analog inputs into
fuzzy variables. These variables are produced by using membership functions (MF); (b) the residual
evaluation step is based RNN. The inputs of the network are the fuzzifier residues (three membership
functions for each residue) and in the outputs we have the decisions.
3.2.1. Fuzzy variables
Each residual (R1, R2, R3) could be described with three memberships (N= Negative, Z= Zero and
P=Positive). For each residue three membership functions are selected: two functions type trapezoidal and
one function type triangular as shown in Figure 6. For the choice of parameters, many tests are affected. The
linguistic variables describing the fuzzifie residuals are defined by the following membership functions: „„N:
negative residual with trapezoidal MF”, „„Z: zero residual with triangular MF”, „„P: positive residual with
trapezoidal MF”. The universe of discourse has been normalized to [−1, 1] band.
Phase detection
Curren
t
Sensor
Nomina
l model
Fault
Residual
generation
System output
Output
Model
Analyze of
symptom
Exper
t
syste
Residual
Phase of localization
R1
μR1
-1 0 1
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Figure 5. Fuzzy MF of the input R1
Figure 6. Neuro Fuzzy diagnostic scheme
3.2.2. Inference
The residual evaluation step is based RNN. The inputs of the network are the fuzzifie residues (µR1,
µR2, µR3) and in the outputs we have the decisions (D1, D2, D3). The network RNN is consists of: nine
neurons in the input layer representing the inputs of the various possible states of residues at a time (k) (after
fuzzification), four neurons in the hidden layer and three neurons in the output layer. The RNN used in this
simulation study is based on the rules summarized in Table 1 which have been obtained after many
simulation tests. Each row of the inference table represents a rule. Each control rule from Table 1 can be
described using the input variables R1, R2 and R3, and the outputs variables D1, D2 and D3. For example
rule 3 is expressed as follow: If {residual 1 is Positive and residual 2 is Positive and residual 3 is Zero}
THEN sensor 2 is faulty.
Table 1. Inference Table
N N1 Z1 P1 N2 Z2 P2 N3 Z3 P3 D1 D2 D3
1 0 1 0 0 1 0 0 1 0 0 0 0
2 0 0 1 1 0 0 0 1 0 1 0 0
3 0 0 1 0 0 1 0 1 0 0 1 0
4 0 1 0 0 1 0 0 0 1 0 0 1
5 0 0 1 1 0 0 0 0 1 1 0 1
6 0 0 1 0 0 1 0 0 1 0 1 1
7 0 0 1 0 0 1 0 1 0 1 1 0
D1 D2 D3
Fault
Inference: In this step
we will analyze the
fuzzy residue previously
obtained by a neural
network
Inputs
Fuzzification
( Membership function)
µR1 µR2 µR3
R1 R2 R3
Ia
Ib
Sensor
of
current
Residual generation
Induction
motor
MF (N1,
Z1, P1)
MF (N2,
Z2, P2)
MF (N3,
Z3, P3)
R1
μR1
-1 0 1
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The mathematical model of a neuron is given by:
1
( ) ( )
N
i i
i
D i µ w R b
Where (R1, R2, R3) are inputs signal of the neuron, (w1, w2,… wN) are the corresponding weights and b is the
bias of the neuron, µ is the tangent sigmoid function and y is the output signal of the neuron. The most
popular supervised training algorithm is the back-propagation [13], which consists of a forward and
backward action. In the first, the free parameters of the network are fixed, and the input signal is propagated
through the network layer by layer. The forward phase finishes with the computation of a mean square error.
Once the ANN is trained properly, it should be adequately tested with intermediate data to verify that training
is correct and complete.
4. DEVELOPMENT of the PROPOSED NEURO FUZZY LOGIC DIAGNOSIS ARCHITECTURE
4.1. Presentation of Xilinx System Generator
Xilinx System Generator Tool developed for Matlab Simulink package is widely used for algorithm
development and verification purposes in Digital Signal Processors (DSP) and Field Programmable Gate
Arrays (FPGAs). Xilinx System Generator (XSG) a high-level tool for designing high-performance DSP
systems under Simulink environment, It is a highly desirable to have this simulation tool that can easily make
the direct translation into hardware of control algorithms with no-knowledge of any Hardware Description
Language (HDL). System Generator Tool allows an abstraction level algorithm development while keeping
the traditional Simulink blocksets, but at the same time automatically translating designs into hardware
implementations that are faithful, synthesizable, and efficient. For rapid prototyping, the choice of this tool is
easily explained by the advantage to simulate the control algorithm is the possibility to generate code that can
be used to program an FPGA directly from the simulation model. When the control algorithm design of the
controller is completed in Matlab Simulink environment by using Xilinx System Generator, it can be
translated automatically into VHDL programming language and then can be embedded into the Xilinx FPGA
application board.
4.2. Fuzzification Block
To evaluate the rule premise, it is necessary to calculate the value of membership of each input to a
specified MF. The residual R1 is represented by three fuzzy set, as shown in Figure 6. For this input we
have 2 mathematical functions depending: trapezoidal function and triangular function. The trapezoidal curve
depends on four scalar parameters a, b, c, and d, as given by,
f(x,a,b,c,d)=
{ }
This Equation is implemented in the hardware using substractors, multipliers and comparator as shown in
Figure 7. The fuzzification process is performed using three fuzzifie units. The fuzzifie block of R1, the
fuzzifie block of R2 and the fuzifie block of R3 takes the input and produces three output values.
(6)
(7)
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Figure 7. Fuzzifier unit of R1.
4.3. Inference
The hardware implementation of the inference block, as shown in Figure 8, accepts three inputs
(µR1, µR2,µR3) from the fuzzification block. The neural processing propagates the inputs to outputs (D1, D2,
D3). Propagation occurs through the different layers of neurons, each neuron Nm,j of the layer m calculates the
output Xm,j. The layer module is made basic unit of the neuron. In effect, each layer is composed of several
neurons operating in parallel. That is why our approach to description of the neuron module is designed in
compliance with the constraint of reusability. In the case of this work we developed our three layers forming
the neural network. The first hidden layer contains 9 neurons. The second layer comprises 4 neurons. The
processing in this block is similar to that determined in the first layer. The internal structure of a neuron is
composed of a set of adders, multipliers and comparator. The third layer contains only three neurons (the
output layer). This last layer detrmine the sensor which is defected; The mathematical processing in this
block is similar to that determined later.
Figure 8. Structure of a neuron of the second layer.
5. Simulation and Interpretation Results
Figure 9 showed the model that uses the Xilinx blocksets for tolerant control. This model is used for
co-simulation. Once the design is verified, a hardware co-simulation block can be generated and then it will
be used to program the FPGA. The System Generator will first download the bit stream. When the download
is complete, System Generators read the inputs from Simulink simulation environment and send them to the
design on the board using the JTAG connection. System Generator then reads the output back from JTAG
and sends it to Simulink for displayed.
To study the performance of this approach, the simulation of the system was conducted using
MATLAB. Motors parameters for simulation are given in Table 2. The simulation results are shown in
Figures 10-12. The torque and flux references that are used in the simulation results of the DTC-SVM
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strategy are 10 N · m and 0.91Wb, respectively. The sampling period of the system is 50 µs. Results using
hardware co-simulation is presented to assess the ability of this diagnosis approach based Neuro Fuzzy
technique to detect and isolate sensor faults in an induction motor. Simulation is carried out with 500 V and
50 Hz sinusoidal inputs. Figure 10 shows speed, torque and current.
Figure 9. The hardware Co-simulation block.
The machine parameters used for simulation are given in Table 2. Various simulation tests have
been performed in order to validate the efficiently of this diagnosis scheme and the results are quite
conclusive. Bias and drift type sensor faults are introduced during steady state conditions of the system.
For illustrative purposes only a few fault scenarios summarized in Tables 3 and 4 are discussed.
Case 1: A bias type fault is injected on sensor 1 as described in Table 3. The corresponding residuals
are shown in Figure 11. Although a single fault may induce changes in several residuals. The decision
functions ensure successful detection and isolation of the fault on sensor 1 as shown in Figure 11. The Neuro-
Fuzzy classifier has been trained to recognize the faulty situations from the fuzzifie residual patterns
according to the rule base given in Table 1.
Case 2: This fault scenario of bias faults on sensors 1 and 2 is described in Table 4. The residual and
the corresponding decision functions are shown in Figure 12. The faulty sensors are promptly detected and
correctly isolated.
Table 2. Induction machine parameters
Voltage 220/380 v
Stator resistance Rs 5.717 Ω
Rotor resistance Rr 4.282 Ω
Stator inductance Ls 0.464 H
Rotor inductance Lr 0.464 H
Mutual inductance M 0.441 H
Moment of inertia J 0.0049 Kg.m2
Figure 10. (a) Speed(rad/s),(b) torque(N/m) and (c) current(A)
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Figure 11. Faculty residuals and corresponding decisions using XSG
Figure 12. Faculty residuals and corresponding decisions using XSG
Table 3.CASE 1
Sensor N Fault time Bias fault
1 1 0.15
Table 4. CASE 2
Sensor N Fault time Bias fault
1 1 0.4
2 1.5 1
6. CONCLUSION
This paper proposed a new current sensor fault detection and isolation algorithm for electrical
drives. The design was based on intelligent technique. The developed FDI algorithm is available for any
current sensor in power converters or electrical drives. The innovative FDI algorithm proposed in this paper
does not require the knowledge of the system model and only concerned sensor outputs are required. The
proposed FDI scheme is based on a two step procedure: a Neural Network is used for residual generation and
a fuzzy neural network performs the residual evaluation task. The successful results obtained in simulation
demonstrate the efficiency of this neuro-fuzzy diagnosis scheme to detect and isolate bias and drift sensor
faults in an induction motor.
REFERENCES
[1] X. S. Li, et al., "Analysis and Simplification of Three-Dimensional Space Vector PWM for Three-Phase Four-Leg
Inverters," IEEE Transactions on Industrial Electronics, vol. 58, pp. 450-464, Feb 2011.
[2] B. Justus Rabi, et al., “Fault Tolerant Control in Z-Source Inverter Fed Induction Motor ", International Journal
of Power Electronics and Drive Systems, pp. 29- 35, 2011.
[3] W.Yun-liang, G. Qi-liang, “Hysteresis Current Control technique based on Space Vector Modulation for Active
Power Filter”, International Journal of Power Electronics and Drive Systems, pp. 1- 6, 2011.
[4] K. Srinivasan, S. Vijayan, S. Paramasivam, K. Sundaramoorthi, “Power Quality Analysis of Vienna Rectifier for
BLDC motor Drive Application", International Journal of Power Electronics and Drive Systems, pp. 7-1 6, 2016.
[5] H.Berriri, “Easy and Fast Sensor Fault Detection and Isolation Algorithm for Electrical Drives”, IEEE transactions
on power electronics, vol. 27, no. 2, February 2012.
11. IJPEDS ISSN: 2088-8694
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[6] P.Rosa; C. Silvestre; P.Oliveira, "Fault Detection and Isolation in Inertial Measurement Units Based on bounding
Sets”, IEEE Control Systems Society, October 2014.
[7] Y. Quan; A. Aitouche; B.O. Bouamama, " Fault detection and isolation of PEM fuel cell system by analytical
redundancy”, IEEE conference publications, pp. 1371 – 1376, 2010.
[8] G. Ablay, " An observer-based fault diagnosis in battery systems of hybrid vehicles”, Electrical and Electronics
Engineering, 2013.
[9] S.Tornil Sin; C. Ocampo Martinez; V. Puig; T. Escobet, "Robust Fault Diagnosis of Nonlinear Systems Using
Interval Constraint Satisfaction and Analytical Redundancy Relations “, IEEE journals & magazines, 2014.
[10] Zhirabok AN, "Nonlinear parity relations: a logic-dynamic approach”, Automation and Remote Control, vol.69, pp
1051-1064, 2008.
[11] H. Ferdowsi," An Online Outlier Identification and Removal Scheme for Improving Fault Detection Performance”,
Neural Networks and Learning Systems, 2013.
[12] O.Obst, "Distributed Fault Detection in Sensor Networks using a Recurrent Neural Network.” Neural Processing
Letters, 2014.
[13] Samy I, Postlethwaite I, "Sensor fault detection and accommodation using neural networks with application to a
non-linear unmanned air vehicle model,” Aerospace Engineering, pp. 437-47.
[14] H. Berriri, I. Slama Belkhodja, “Enhanced Parity Equations Method for Sensor Fault Detection in Electrical
Drives,” Conference on Control and Fault-Tolerant Systems, 2010, Nice, France.
BIOGRAPHIES OF AUTHORS
Souha BOUKADIDA received the degree in Electrical Engineering from National School of
Engineering of Monastir, Tunisia in 2012. In 2013 she received his M.S degree in Automatic and
Diagnostic from Moanstir University. Her current research interests include rapid prototyping
and reconfigurable architecture for real-time control applications of electrical system
Soufien GDAIM received the degree in Electrical Engineering from National School of
Engineering of Sfax, Tunisia in 1998. In 2007 he received his M.S degree in electronic and real-
time informatic from Sousse University and received his PhD degree in Electrical Engineering in
2013 from ENIM, Tunisia. His current research interests include rapid prototyping and
reconfigurable architecture for real-time control applications of electrical system.
Abdellatif MTIBAA is currently Professor in Micro-Electronics and Hardware Design with
Electrical Department at the National School of Engineering of Monastir and Head of Circuits
Systems Reconfigurable ENIM-Group at Electronic and microelectronic Laboratory. He holds a
Diploma in Electrical Engineering in 1985 and received his PhD degree in Electrical
Engineering in 2000. His current research interests include System on Programmable Chip, high
level synthesis, rapid prototyping and reconfigurable architecture for real-time multimedia
applications. Dr. Abdellatif Mtibaa has authored/coauthored over 100 papers in international
journals and conferences. He served on the technical program committees for several
international conferences. He also served as a co-organizer of several international conferences