This document discusses condition monitoring of rotating electrical motors using piezoelectric sensors. It presents a simulation model developed to detect problems in motors based on vibration analysis. If vibration exceeds unsatisfactory or unacceptable thresholds, the system will display alerts on a computer screen to indicate defective parts. Fast Fourier Transform (FFT) analysis and Motor Current Signature Analysis (MCSA) are used to diagnose faults in induction motors. The document focuses on developing this condition monitoring system to protect motors from unexpected shutdowns and increase lifetime through early problem detection without requiring human observation.
This document discusses motor current signature analysis (MCSA) for detecting faults in induction motors. MCSA analyzes current signals to identify faults by comparing signatures from healthy and faulty motors. It has advantages over other monitoring methods as it does not require additional sensors. Signal processing techniques like fast Fourier transforms (FFT), short-time Fourier transforms, and wavelet transforms are used to analyze current signals in the frequency domain and detect fault frequencies. An algorithm is presented that uses the standard deviation of wavelet coefficients to detect faults like loose connections or stator resistance unbalancing. MCSA can detect faults at an early stage to prevent further damage.
This document presents a study on using acoustic signal analysis to detect faults in bearings. The study develops an experimental setup to acquire acoustic signals from bearings under different conditions, including with and without defects. The acoustic signals are processed using techniques like fast Fourier transforms and wavelet transforms to extract information about faults. Signals are analyzed from bearings with no defects, misalignment, looseness, missing balls, and combinations of defects. Results show the acoustic signal energy at different frequencies for healthy and faulty bearings. This acoustic signal analysis technique can be used to detect bearing faults and failures.
IRJET- Fuzzy Logic based Fault Detection in Induction Machines using CloudIRJET Journal
This document presents a system for online condition monitoring of induction motors using fuzzy logic and cloud computing. It involves two phases:
1) Developing a simulation model in MATLAB/Simulink to monitor motor parameters and detect faults.
2) Implementing an online condition monitoring system using a Raspberry Pi, sensors to measure motor vibrations, temperature etc., and a cloud platform to remotely store and access data in real-time.
Fuzzy logic is used to analyze sensor data and detect faults based on defined rules and membership functions. The system aims to monitor key parameters of induction motors and identify failures to enable safe and efficient operation in industrial applications.
A robust diagnosis method for speed sensor fault based on stator currents in ...IJECEIAES
The document presents a novel method for diagnosing speed sensor faults in induction motor drive systems based on stator currents. The method compares measured and estimated stator currents, and also checks for differences between measured and reference rotor speeds, to detect speed sensor failures while preventing confusion from current sensor faults. Simulations using MATLAB/Simulink demonstrate the effectiveness of the proposed diagnosis algorithm in detecting speed sensor faults across different speed ranges, including low speeds where sensor signals are often noisy.
Fault Detection and Failure Prediction Using Vibration AnalysisTristan Plante
This document discusses using vibration analysis to detect faults and predict failures in rotating equipment like electric motors. It describes an experiment where vibration data was collected from a motor under normal operation and different fault conditions (unbalance, mechanical looseness, bearing defect). The data was analyzed using spectrum analysis software and MATLAB. Specific fault frequencies were identified that corresponded to the type of fault. The results support using vibration analysis to monitor equipment condition and enable predictive maintenance by detecting issues before catastrophic failures occur.
This document summarizes a line follower robot project submitted for a bachelor's degree. The robot uses infrared sensors to follow a black line on a white surface or vice versa. An AT89C51 microcontroller controls two DC motors based on sensor input to move the robot forward, left, or right. The block diagram and circuit diagram show how the infrared sensor array, microcontroller, motor driver, and motors are connected. Potential applications include maze solving, pick-and-place automation, material placement, and obstacle avoidance.
Abstract Automatic Control of Railway Gatesvishnu murthy
The document describes an automatic control system for railway gates at level crossings. It uses infrared sensors to detect arriving and departing trains and control opening and closing gates via a motor. When the first IR sensor detects a train, traffic signals turn yellow and a buzzer activates. When the second sensor detects the train, signals turn red and the motor closes the gates. The gates reopen when the third sensor detects the train has passed. The system prevents accidents by automating gate operations instead of relying on human gatekeepers. It also uses additional sensors to detect obstacles on the tracks that could prevent gate closure.
Vibration Analysis of Industrial Drive for Broken Bearing Detection Using Pro...IAES-IJPEDS
The document describes a proposed Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system for detecting broken bearings in induction motors used in industrial drives. The system uses biorthogonal wavelet transform on vibration signal data to localize time and frequency domains and identify transient disturbances. It extracts detailed coefficients up to the fifth derivative form. A Posterior Probabilistic Neural Network then detects fault levels faster using the fifth derivative, achieving detection at a constant frequency with minimal execution time. The system aims to reduce current flow and identify faults earlier compared to existing methods. An experiment using Simulink detects healthy and unhealthy motors based on fault detection rate, current flow rate,
This document discusses motor current signature analysis (MCSA) for detecting faults in induction motors. MCSA analyzes current signals to identify faults by comparing signatures from healthy and faulty motors. It has advantages over other monitoring methods as it does not require additional sensors. Signal processing techniques like fast Fourier transforms (FFT), short-time Fourier transforms, and wavelet transforms are used to analyze current signals in the frequency domain and detect fault frequencies. An algorithm is presented that uses the standard deviation of wavelet coefficients to detect faults like loose connections or stator resistance unbalancing. MCSA can detect faults at an early stage to prevent further damage.
This document presents a study on using acoustic signal analysis to detect faults in bearings. The study develops an experimental setup to acquire acoustic signals from bearings under different conditions, including with and without defects. The acoustic signals are processed using techniques like fast Fourier transforms and wavelet transforms to extract information about faults. Signals are analyzed from bearings with no defects, misalignment, looseness, missing balls, and combinations of defects. Results show the acoustic signal energy at different frequencies for healthy and faulty bearings. This acoustic signal analysis technique can be used to detect bearing faults and failures.
IRJET- Fuzzy Logic based Fault Detection in Induction Machines using CloudIRJET Journal
This document presents a system for online condition monitoring of induction motors using fuzzy logic and cloud computing. It involves two phases:
1) Developing a simulation model in MATLAB/Simulink to monitor motor parameters and detect faults.
2) Implementing an online condition monitoring system using a Raspberry Pi, sensors to measure motor vibrations, temperature etc., and a cloud platform to remotely store and access data in real-time.
Fuzzy logic is used to analyze sensor data and detect faults based on defined rules and membership functions. The system aims to monitor key parameters of induction motors and identify failures to enable safe and efficient operation in industrial applications.
A robust diagnosis method for speed sensor fault based on stator currents in ...IJECEIAES
The document presents a novel method for diagnosing speed sensor faults in induction motor drive systems based on stator currents. The method compares measured and estimated stator currents, and also checks for differences between measured and reference rotor speeds, to detect speed sensor failures while preventing confusion from current sensor faults. Simulations using MATLAB/Simulink demonstrate the effectiveness of the proposed diagnosis algorithm in detecting speed sensor faults across different speed ranges, including low speeds where sensor signals are often noisy.
Fault Detection and Failure Prediction Using Vibration AnalysisTristan Plante
This document discusses using vibration analysis to detect faults and predict failures in rotating equipment like electric motors. It describes an experiment where vibration data was collected from a motor under normal operation and different fault conditions (unbalance, mechanical looseness, bearing defect). The data was analyzed using spectrum analysis software and MATLAB. Specific fault frequencies were identified that corresponded to the type of fault. The results support using vibration analysis to monitor equipment condition and enable predictive maintenance by detecting issues before catastrophic failures occur.
This document summarizes a line follower robot project submitted for a bachelor's degree. The robot uses infrared sensors to follow a black line on a white surface or vice versa. An AT89C51 microcontroller controls two DC motors based on sensor input to move the robot forward, left, or right. The block diagram and circuit diagram show how the infrared sensor array, microcontroller, motor driver, and motors are connected. Potential applications include maze solving, pick-and-place automation, material placement, and obstacle avoidance.
Abstract Automatic Control of Railway Gatesvishnu murthy
The document describes an automatic control system for railway gates at level crossings. It uses infrared sensors to detect arriving and departing trains and control opening and closing gates via a motor. When the first IR sensor detects a train, traffic signals turn yellow and a buzzer activates. When the second sensor detects the train, signals turn red and the motor closes the gates. The gates reopen when the third sensor detects the train has passed. The system prevents accidents by automating gate operations instead of relying on human gatekeepers. It also uses additional sensors to detect obstacles on the tracks that could prevent gate closure.
Vibration Analysis of Industrial Drive for Broken Bearing Detection Using Pro...IAES-IJPEDS
The document describes a proposed Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system for detecting broken bearings in induction motors used in industrial drives. The system uses biorthogonal wavelet transform on vibration signal data to localize time and frequency domains and identify transient disturbances. It extracts detailed coefficients up to the fifth derivative form. A Posterior Probabilistic Neural Network then detects fault levels faster using the fifth derivative, achieving detection at a constant frequency with minimal execution time. The system aims to reduce current flow and identify faults earlier compared to existing methods. An experiment using Simulink detects healthy and unhealthy motors based on fault detection rate, current flow rate,
This document describes a study that developed an Internet of Things (IoT) based electromyography (EMG) monitoring device to analyze muscle fatigue in the biceps brachii muscle during manual lifting tasks. EMG signals were recorded from four male participants performing repetitive lifting and divided into four phases. The mean power frequency of the signals was calculated to evaluate muscle activity and fatigue in each phase. A WiFi module was also added to transmit the raw EMG data over the internet using TCP/IP protocol, making the device an IoT device. The results showed that phase 2, lifting the weight, experienced the most muscle fatigue compared to the other phases. The study concluded that repetitive manual lifting leads to fatigue in all muscles
INTELLIGENT TRAIN ENGINE PROJECT.
THIS PROJECT IS ABOUT THREE APPLICATIONS IN RAILWAY SYSTEM.
THOSE ARE
1.OBSTACLES DETECTION ON THE RAILWAY TRACKS USING ULTRASONIC SENSORS AND TRAIN ENGINE SPEED CONTROLLING.
2.FIRE DETECTION IN COACHES USING SMOKE SENSORS AND DISPLAY ABOUT FIRE IN TRAIN ENGINE.
3.AUTOMATIC RAILWAY CROSSING GATES CLOSING AND OPENING WHEN TRAIN CROSSING USING IR SENSORS AND ALARM SYSTEM.
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.
This document contains a bio-data and project proposal for a device called "Railway Level Crossing Accidents Preventer" submitted by S.Sahaya Justus Antony. The proposal includes an abstract describing the objective to create a fully automated railway crossing. It also includes sections on the introduction, block description, list of figures, and conclusion. The introduction describes how sensors would detect an approaching train and stop vehicles from crossing, then allow vehicles to pass after the train clears. The block description outlines the main components including a microcontroller, RF transmitter, RF receiver, and power supply.
Asymmetrical fault detection in de energized distribution feedereSAT Journals
Abstract After maintenance or repairing of the de-energized distribution feeder there is need of safely energizing of feeder for the utility’s safety. The safely energizing can be done by determining the fault exists on the distribution system before energizing the system again. The fault detection in de-energized distribution feeder is more difficult than the energized distribution feeder since it requires the system level voltage production and execution to the downstream. Here we implemented an asymmetrical fault detection method to detect the fault before re-energizing the distribution feeder. A controllable signal is feed into de-energized distribution feeder using a thyristor based device to generate the electrical response. The strength of signal can be adjusted from low to high to detect low impedance fault at the beginning, since the maximum faults on distribution system are low impedance faults. A low strength signal may act as an alarm to the personnel or animal in contact with the live part of the system so that they can get away from the system to avoid getting sudden electric shock. Also the major faults on distribution systems are asymmetrical faults so it is necessary to identify and detect the asymmetrical faults before Re-energizing the feeder. The detection and classification of different asymmetrical faults is also explained in this paper. For the determination of the faults we are analyzing the voltage and current signals of the downstream feeder. The fault detection algorithm and control strategies of thyristors are also described for different faults and analyzed by using computer simulation in MATLAB. Keywords: Fault Detection, Fault Classification, De-Energized Distribution Feeder
IRJET- Design of a Portable Contact-Less Tachometer using Infrared Sensor for...IRJET Journal
This document describes the design of a portable contactless tachometer using an infrared sensor for laboratory applications. The tachometer uses an Arduino Uno microcontroller, infrared sensor to detect rotations, and a 16x2 LCD display to show revolutions per minute (RPM). It works by counting the number of times the infrared sensor detects the rotating object within a set time period. This allows it to measure RPM without direct contact, making it useful for industrial and laboratory speed measurement of motors and other rotating devices in a simple and affordable way.
This document contains a syllabus for the course ME407 Mechatronics taught by Sukesh O P. The syllabus covers various topics related to mechatronics including sensors, actuators, microelectromechanical systems, mechatronics applications in CNC machines and robotics. It also provides details of course modules which discuss different types of sensors like encoders, resolvers, synchros and vibration sensors along with principles and working.
This document outlines the course objectives, expected outcomes, syllabus, and content for the ME407 Mechatronics course taught by Sukesh O P. The course aims to introduce sensors used in CNC machines and robots, study MEMS sensors, and develop hydraulic/pneumatic circuits and PLC programs. By the end, students will be able to know mechanical systems in mechatronics and integrate various engineering disciplines in mechatronic design. The syllabus covers introduction to mechatronics, sensors, actuators, MEMS, applications in CNC and robotics.
This project report describes a wireless automatic railway gate controlling system that uses sensors and a microcontroller to open and close railway gates automatically. The system aims to reduce accidents by providing reliable automatic operation of gates without human errors, and to reduce the time taken to open and close gates. Key elements include motion sensors to detect approaching trains, an IR circuit, and a microcontroller to control the automatic operation of the railway gates.
Health Monitoring of Industrial and Electrical EquipmentMAJAHARUL IMAM
It Detects if motor, generator or any Industrial Equipments having any faults,
excess heating and more vibration. Then sound up alarm to minimize the problems
automatic railway gate control system using arduinoantivirusspam
The objective of this project is to manage the control system of railway gate using the arduino. When train arrives at the sensing point alarm is triggered at the railway crossing point so that the people get intimation that gate is going to be closed. Then the control system activates and closes the gate on either side of the track once the train crosses the other end control system automatically lifts the gate.
Rotating machine fault detection using principal component analysis of vibrat...Tristan Plante
This document discusses using principal component analysis (PCA) to automate fault detection in rotating machinery based on vibration analysis. An experiment was conducted using a machinery fault simulator to collect vibration data under healthy, unbalanced, and misaligned conditions. PCA was then used to analyze the fast Fourier transform (FFT) data to identify patterns associated with each fault type. The results showed that PCA successfully identified and grouped the healthy, unbalanced, and misaligned conditions. Therefore, PCA has potential for automating vibration-based fault detection and reducing maintenance costs.
This document proposes an automatic control system for unmanned railway gates using sensors to reduce accidents. The objectives are to decrease costs by automating gates and reducing accidents through automatic closure when trains approach. The methodology uses infrared sensors to detect approaching trains and microcontrollers to signal gate motors. When a train is sensed, the system checks for vehicles near the gate before closing it, and reopens the gate once the train passes. This system could automate gates at road-rail crossings in Pakistan to improve safety.
The document describes an automatic railway gate control system that uses sensors and a microcontroller to operate railway crossing gates. When a train is detected by infrared sensors, an alarm is triggered and the microcontroller then controls stepper motors to close the gates. The system uses an AT89C51 microcontroller, infrared sensors for train detection, stepper motors to move the gates, and a power supply to power the electrical components. Keil Microvision IDE is used for programming the microcontroller.
This document describes digital transducers and their applications. Digital transducers directly produce a digital output signal without requiring analog-to-digital conversion. Some common types of digital transducers discussed are shaft encoders, digital resolvers, digital tachometers, and Hall effect sensors. Shaft encoders can provide measurements of angular position and velocity and are widely used in applications like robotics and machine tools. Digital transducers offer advantages like ease of generating and manipulating digital signals and improved noise immunity during long-distance signal transmission.
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.
This document describes an automatic railway gate crossing and track switching system using a microcontroller. It aims to improve safety by preventing collisions through anti-collision techniques and automatic control. Sensors are used to detect train positions and speeds in order to calculate the timing of automatic gate closure and track switching. The system is designed to avoid both head-on and rear-end collisions through predictive position sensing and switching trains to alternate tracks when collisions are detected.
Obstacle Avoidance Robot Summer training Presentation Wasi Abbas
i did an extremely hard work on it. I believe that you all my friends will surely get the benefit of this presentation. As a student of B.tech I just wish to assist those who always ready to assist another one. thanks for reading......
Warning System for Unmanned Railway CrossingsVishesh Banga
We come across many railway accidents occurring at unmanned railway crossings due to carelessness in manual operations or lack of workers
Railroad related accidents are more dangerous than other transportation accidents in terms of severity and death rate etc.
We, in this project has come up with a solution for the same.
The Automatic railway gate control system by android remote control is used to operate and control unmanned railway gate in order to avoid train accidents.
This document summarizes research on using the WAD (Wavelet Analysis, Dyadic Transformation, and Adaptive Neuro-Fuzzy Inference System) technique to detect faults in electric motors for the purpose of automatic speed control. The researchers designed hardware with a MEMS vibration sensor and microcontroller to acquire motor vibration signals. They then used MATLAB to process the signals using WAD. Results showed WAD could accurately detect faults by identifying error frequencies. Specifically, ANFIS provided more accurate fault identification than wavelet or dyadic transforms alone, reducing error by 30-40%. The research aims to help prevent motor faults from disrupting industrial processes through automatic speed control based on fault detection.
1) The document discusses using discrete wavelet transforms to analyze vibration signals from roller bearings to detect faults. It proposes a new feature - summing the squared wavelet decomposition coefficients at each level - and compares it to the traditional energy-based feature.
2) An experiment is described where vibration signals are collected from a test rig under normal conditions and with introduced inner race, outer race, and combined faults. The signals are decomposed using discrete wavelet transforms.
3) Features are then extracted from the wavelet decompositions using both the proposed summed squared coefficient feature and the traditional energy-based feature. A decision tree is used to classify the features and determine which feature performs better at detecting the faults.
This document describes a study that developed an Internet of Things (IoT) based electromyography (EMG) monitoring device to analyze muscle fatigue in the biceps brachii muscle during manual lifting tasks. EMG signals were recorded from four male participants performing repetitive lifting and divided into four phases. The mean power frequency of the signals was calculated to evaluate muscle activity and fatigue in each phase. A WiFi module was also added to transmit the raw EMG data over the internet using TCP/IP protocol, making the device an IoT device. The results showed that phase 2, lifting the weight, experienced the most muscle fatigue compared to the other phases. The study concluded that repetitive manual lifting leads to fatigue in all muscles
INTELLIGENT TRAIN ENGINE PROJECT.
THIS PROJECT IS ABOUT THREE APPLICATIONS IN RAILWAY SYSTEM.
THOSE ARE
1.OBSTACLES DETECTION ON THE RAILWAY TRACKS USING ULTRASONIC SENSORS AND TRAIN ENGINE SPEED CONTROLLING.
2.FIRE DETECTION IN COACHES USING SMOKE SENSORS AND DISPLAY ABOUT FIRE IN TRAIN ENGINE.
3.AUTOMATIC RAILWAY CROSSING GATES CLOSING AND OPENING WHEN TRAIN CROSSING USING IR SENSORS AND ALARM SYSTEM.
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.
This document contains a bio-data and project proposal for a device called "Railway Level Crossing Accidents Preventer" submitted by S.Sahaya Justus Antony. The proposal includes an abstract describing the objective to create a fully automated railway crossing. It also includes sections on the introduction, block description, list of figures, and conclusion. The introduction describes how sensors would detect an approaching train and stop vehicles from crossing, then allow vehicles to pass after the train clears. The block description outlines the main components including a microcontroller, RF transmitter, RF receiver, and power supply.
Asymmetrical fault detection in de energized distribution feedereSAT Journals
Abstract After maintenance or repairing of the de-energized distribution feeder there is need of safely energizing of feeder for the utility’s safety. The safely energizing can be done by determining the fault exists on the distribution system before energizing the system again. The fault detection in de-energized distribution feeder is more difficult than the energized distribution feeder since it requires the system level voltage production and execution to the downstream. Here we implemented an asymmetrical fault detection method to detect the fault before re-energizing the distribution feeder. A controllable signal is feed into de-energized distribution feeder using a thyristor based device to generate the electrical response. The strength of signal can be adjusted from low to high to detect low impedance fault at the beginning, since the maximum faults on distribution system are low impedance faults. A low strength signal may act as an alarm to the personnel or animal in contact with the live part of the system so that they can get away from the system to avoid getting sudden electric shock. Also the major faults on distribution systems are asymmetrical faults so it is necessary to identify and detect the asymmetrical faults before Re-energizing the feeder. The detection and classification of different asymmetrical faults is also explained in this paper. For the determination of the faults we are analyzing the voltage and current signals of the downstream feeder. The fault detection algorithm and control strategies of thyristors are also described for different faults and analyzed by using computer simulation in MATLAB. Keywords: Fault Detection, Fault Classification, De-Energized Distribution Feeder
IRJET- Design of a Portable Contact-Less Tachometer using Infrared Sensor for...IRJET Journal
This document describes the design of a portable contactless tachometer using an infrared sensor for laboratory applications. The tachometer uses an Arduino Uno microcontroller, infrared sensor to detect rotations, and a 16x2 LCD display to show revolutions per minute (RPM). It works by counting the number of times the infrared sensor detects the rotating object within a set time period. This allows it to measure RPM without direct contact, making it useful for industrial and laboratory speed measurement of motors and other rotating devices in a simple and affordable way.
This document contains a syllabus for the course ME407 Mechatronics taught by Sukesh O P. The syllabus covers various topics related to mechatronics including sensors, actuators, microelectromechanical systems, mechatronics applications in CNC machines and robotics. It also provides details of course modules which discuss different types of sensors like encoders, resolvers, synchros and vibration sensors along with principles and working.
This document outlines the course objectives, expected outcomes, syllabus, and content for the ME407 Mechatronics course taught by Sukesh O P. The course aims to introduce sensors used in CNC machines and robots, study MEMS sensors, and develop hydraulic/pneumatic circuits and PLC programs. By the end, students will be able to know mechanical systems in mechatronics and integrate various engineering disciplines in mechatronic design. The syllabus covers introduction to mechatronics, sensors, actuators, MEMS, applications in CNC and robotics.
This project report describes a wireless automatic railway gate controlling system that uses sensors and a microcontroller to open and close railway gates automatically. The system aims to reduce accidents by providing reliable automatic operation of gates without human errors, and to reduce the time taken to open and close gates. Key elements include motion sensors to detect approaching trains, an IR circuit, and a microcontroller to control the automatic operation of the railway gates.
Health Monitoring of Industrial and Electrical EquipmentMAJAHARUL IMAM
It Detects if motor, generator or any Industrial Equipments having any faults,
excess heating and more vibration. Then sound up alarm to minimize the problems
automatic railway gate control system using arduinoantivirusspam
The objective of this project is to manage the control system of railway gate using the arduino. When train arrives at the sensing point alarm is triggered at the railway crossing point so that the people get intimation that gate is going to be closed. Then the control system activates and closes the gate on either side of the track once the train crosses the other end control system automatically lifts the gate.
Rotating machine fault detection using principal component analysis of vibrat...Tristan Plante
This document discusses using principal component analysis (PCA) to automate fault detection in rotating machinery based on vibration analysis. An experiment was conducted using a machinery fault simulator to collect vibration data under healthy, unbalanced, and misaligned conditions. PCA was then used to analyze the fast Fourier transform (FFT) data to identify patterns associated with each fault type. The results showed that PCA successfully identified and grouped the healthy, unbalanced, and misaligned conditions. Therefore, PCA has potential for automating vibration-based fault detection and reducing maintenance costs.
This document proposes an automatic control system for unmanned railway gates using sensors to reduce accidents. The objectives are to decrease costs by automating gates and reducing accidents through automatic closure when trains approach. The methodology uses infrared sensors to detect approaching trains and microcontrollers to signal gate motors. When a train is sensed, the system checks for vehicles near the gate before closing it, and reopens the gate once the train passes. This system could automate gates at road-rail crossings in Pakistan to improve safety.
The document describes an automatic railway gate control system that uses sensors and a microcontroller to operate railway crossing gates. When a train is detected by infrared sensors, an alarm is triggered and the microcontroller then controls stepper motors to close the gates. The system uses an AT89C51 microcontroller, infrared sensors for train detection, stepper motors to move the gates, and a power supply to power the electrical components. Keil Microvision IDE is used for programming the microcontroller.
This document describes digital transducers and their applications. Digital transducers directly produce a digital output signal without requiring analog-to-digital conversion. Some common types of digital transducers discussed are shaft encoders, digital resolvers, digital tachometers, and Hall effect sensors. Shaft encoders can provide measurements of angular position and velocity and are widely used in applications like robotics and machine tools. Digital transducers offer advantages like ease of generating and manipulating digital signals and improved noise immunity during long-distance signal transmission.
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.
This document describes an automatic railway gate crossing and track switching system using a microcontroller. It aims to improve safety by preventing collisions through anti-collision techniques and automatic control. Sensors are used to detect train positions and speeds in order to calculate the timing of automatic gate closure and track switching. The system is designed to avoid both head-on and rear-end collisions through predictive position sensing and switching trains to alternate tracks when collisions are detected.
Obstacle Avoidance Robot Summer training Presentation Wasi Abbas
i did an extremely hard work on it. I believe that you all my friends will surely get the benefit of this presentation. As a student of B.tech I just wish to assist those who always ready to assist another one. thanks for reading......
Warning System for Unmanned Railway CrossingsVishesh Banga
We come across many railway accidents occurring at unmanned railway crossings due to carelessness in manual operations or lack of workers
Railroad related accidents are more dangerous than other transportation accidents in terms of severity and death rate etc.
We, in this project has come up with a solution for the same.
The Automatic railway gate control system by android remote control is used to operate and control unmanned railway gate in order to avoid train accidents.
This document summarizes research on using the WAD (Wavelet Analysis, Dyadic Transformation, and Adaptive Neuro-Fuzzy Inference System) technique to detect faults in electric motors for the purpose of automatic speed control. The researchers designed hardware with a MEMS vibration sensor and microcontroller to acquire motor vibration signals. They then used MATLAB to process the signals using WAD. Results showed WAD could accurately detect faults by identifying error frequencies. Specifically, ANFIS provided more accurate fault identification than wavelet or dyadic transforms alone, reducing error by 30-40%. The research aims to help prevent motor faults from disrupting industrial processes through automatic speed control based on fault detection.
1) The document discusses using discrete wavelet transforms to analyze vibration signals from roller bearings to detect faults. It proposes a new feature - summing the squared wavelet decomposition coefficients at each level - and compares it to the traditional energy-based feature.
2) An experiment is described where vibration signals are collected from a test rig under normal conditions and with introduced inner race, outer race, and combined faults. The signals are decomposed using discrete wavelet transforms.
3) Features are then extracted from the wavelet decompositions using both the proposed summed squared coefficient feature and the traditional energy-based feature. A decision tree is used to classify the features and determine which feature performs better at detecting the faults.
A Survey on Classification of Power Quality Disturbances in a Power SystemIJERA Editor
This document provides a survey of techniques for classifying power quality disturbances in a power system. It discusses various power quality issues and types of disturbances such as transients, interruptions, sags, swells, waveform distortions, and frequency variations. It then describes several signal processing techniques used for feature extraction, including Fourier transform, short-time Fourier transform, S-transform, Hilbert-Huang transform, Kalman filter, and wavelet transform. Finally, it reviews various classification methods such as artificial neural networks, fuzzy expert systems, adaptive neuro-fuzzy systems, genetic algorithms, and support vector machines that have been applied to classify power quality disturbances.
This document summarizes a research paper on using MEMS sensors and neural networks to detect faults in the motors of wind turbines. It begins with an abstract that overviews using an accelerometer sensor to detect vibrations in the motor and send the data to a control unit. It then provides background on existing vibration-based fault detection methods and proposes a new method using MEMS sensors, wavelet packet transform analysis of the sensor data, and a neural network classifier to detect faults at an early stage. The document concludes that this method allows accurate and reliable condition monitoring of wind turbines to prevent motor damage.
Condition monitoring of induction motor with a case studyIAEME Publication
This document summarizes a study on condition monitoring of an induction motor. The study utilized multiple monitoring techniques including temperature monitoring, vibration analysis, motor current signature analysis, and shaft voltage measurement. Temperature, vibration, and shaft voltage readings were found to be within normal limits, indicating the motor was in good health. Motor current signature analysis detected no issues, further confirming the healthy state of the motor. The study demonstrated how a combination of condition monitoring techniques can evaluate the overall condition and help plan preventive maintenance for motors.
Condition monitoring of induction motor with a case studyIAEME Publication
This document summarizes a study on condition monitoring of an induction motor. It discusses various monitoring methods like temperature monitoring, vibration analysis, motor current signature analysis, and shaft voltage measurement. Temperature monitoring identified hotspots indicating potential insulation or cooling issues. Vibration analysis found peaks corresponding to unbalance, misalignment, and bearing or looseness issues. Motor current signature analysis identified rotor bar and joint issues by analyzing current waveforms. Together these methods provided a comprehensive assessment of the motor's health to guide maintenance.
IOT Based Machine Health Monitoring SystemIRJET Journal
This document presents a machine health monitoring system developed using Internet of Things (IoT) technology. The system monitors key parameters of 3-phase industrial machines such as voltage, current, temperature, speed and vibration using sensors. It has three units - an indicating unit to display electrical parameters, a sensing unit to monitor parameters and set standard ratings, and a controlling unit to automatically turn the machine on or off based on the parameter readings. If a fault is detected, it sends an SMS alert to the operator. The system aims to minimize production losses by detecting minor faults early and preventing machine breakdown. It could benefit many small and medium manufacturing plants by providing a low-cost, automated health monitoring and maintenance tool.
This document provides details about a wireless data acquisition system for induction motors, including previous work, progress made, and system components. It describes using a ZigBee network to wirelessly monitor and acquire current, voltage, speed, and temperature data from a single-phase induction motor. Sensors include current transformers, potential transformers, and an encoder. An Atmel microcontroller processes the data, which is displayed using Delphi software. If any measured parameter exceeds set limits, the motor is stopped and an error message is shown.
Transformer monitoring and controlling with GSM based systemIRJET Journal
This document describes a proposed system for monitoring and controlling a distribution transformer using GSM technology. The system would monitor key parameters like voltage, current, temperature, oil level and detect any issues. Sensors would collect this data and send it to an Arduino controller. The controller would analyze the data and if any problems were detected, it would send an alert message using a GSM modem to notify operators remotely. This system aims to monitor transformers in real-time to detect issues early and prevent failures, allowing for more efficient maintenance and reducing costs. It could provide parameter updates at regular intervals to a control station for monitoring transformer health remotely.
Induction Motor Fault Diagnostics using Fuzzy SystemIRJET Journal
This document describes a system for detecting faults in induction motors using fuzzy logic. It involves developing a virtual fault simulator in LabVIEW to generate current signals corresponding to different motor faults. A virtual fault analyzer acquires the current signals, performs spectral analysis to identify fault frequencies, and uses a fuzzy inference system to analyze the data and diagnose the type of fault. The system is able to detect common faults such as rotor bar failures, load fluctuations, and unbalanced supply voltage. However, further work is needed to refine the system for online monitoring and address limitations before real-time validation.
MRA Analysis for Faults Indentification in Multilevel InverterIRJET Journal
This document proposes using wavelet analysis to detect and identify switch faults in a diode-clamped multilevel inverter feeding an induction motor drive. A wavelet-based multi-resolution analysis is used to analyze voltage and current signals from the system under normal and faulty conditions. Signatures extracted from the wavelet analysis at different resolution levels can be used to develop a feature vector to discriminate between healthy and faulty systems, and identify the type of fault. The analysis is able to detect switch shorts, opens, increased load, and line-to-line faults based on variations in the wavelet transform details of signals like phase voltage, line current, and switch voltages.
Various and multilevel of wavelet transform for classification misalignment o...TELKOMNIKA JOURNAL
Induction motors have become a major part of the industry because of strong construction, cheap in purchasing and maintenance, high efficiency, and easy to operate. Preventive maintenance must always be carried out on all industrial equipment, including induction motors to last long and prevent further damage. Based on research in the industry, around 42%-50% or almost 50% is bearing damage. One reason is the occurrence of misalignment during the installation of the load on the induction motor. This study tries to identify the condition of the motor and classify the level of misalignment damage that occurs. In the process, the mother wavelet like as Daubechis, Symlet and Coiflet discrete wavelet transform (DWT) are selected as tools in processing motor vibration data. The level of DWT applied is 1st to 3rd level. Then, the three types of signal extraction, namely sum, range, and energy, which are obtained from a high-frequency signal of DWT, are used as input to Quadratic and Linear Discriminant Analysis. Then, discriminant analysis analyzes and classifies them into normal operation and two misalignments conditions. The simulation shows that 1st level of Daubechis DWT combined with quadratic discriminant analysis generates the best classification. It results 0% error of classification with Db3, Db4 and Db5, 4.17% error with Db1 and 8.33% error with Db2.
ESPRIT Method Enhancement for Real-time Wind Turbine Fault RecognitionIAES-IJPEDS
Early fault diagnosis plays a very important role in the modern energy production systems. The wind turbine machine requires a regular maintenance to guarantee an acceptable lifetime and to minimize production loss. In order to implement a fast, proactive condition monitoring, ESPRIT- TLS method seems the correct choice due to its robustness in improving the frequency and amplitude detection. Nevertheless, it has a very complex computation to implement in real time. To avoid this problem, a Fast- ESPRIT algorithm that combined the IIR band-pass filtering technique, the decimation technique and the original ESPRIT-TLS method were employed to enhance extracting accurately frequencies and their magnitudes from the wind stator current. The proposed algorithm has been evaluated by computer simulations with many fault scenarios. Study results demonstrate the performance of Fast-ESPRIT allowing fast and high resolution harmonics identification with minimum computation time and less memory cost.
Characterization of transients and fault diagnosis in transformer by discreteIAEME Publication
This document discusses using discrete wavelet transform (DWT) and artificial neural networks (ANN) to characterize transients and diagnose faults in transformers. It begins with an introduction to the problem and background on using the second harmonic component for discrimination. It then discusses why time-frequency information is needed and the advantages of wavelet transforms over Fourier transforms. The document describes collecting data from a test transformer under normal and faulted conditions. It explains using DWT for feature extraction and visualizing the wavelet decomposition levels to characterize magnetizing inrush versus inter-turn faults. Finally, it proposes using ANN trained on the wavelet spectral energies for automated discrimination between fault cases.
Developing Infrared Controlled Automated Door SystemIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
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.
This document presents a system called the Electromagnetic Accident Avoiding System that is intended to reduce road accidents. The system uses an electromagnetic cylinder actuator to control a vehicle's bumper. Ultrasonic and PIR sensors detect obstacles and determine if they are living or non-living. If a non-living obstacle is detected, the electromagnetic cylinder actuates to extend the bumper forward to absorb impact forces during a collision. The system is designed to reduce the frequency and severity of accidents on roads by dissipating impact forces when vehicles collide with stationary objects.
ANN Approach for Fault Classification in Induction Motors using Current and V...IRJET Journal
This document discusses using an artificial neural network (ANN) approach to classify faults in induction motors based on current and voltage signals. It proposes using negative sequence current and swing angle values extracted from motor signals as inputs to a multi-layer perceptron ANN for fault classification. The faults considered are the healthy condition, rotor broken bar fault, and stator inter-turn short circuit fault. Experimental data was collected from a test motor under these different conditions to train and evaluate the ANN's performance at fault classification.
IRJET- Modelling and Condition Monitoring of 3훟 Induction Motor using Fuzzy L...IRJET Journal
This document presents a MATLAB model and simulation of a 3-phase induction motor for condition monitoring using fuzzy logic. The model monitors for common faults like stator winding issues, voltage imbalances, and phase faults. Fuzzy logic membership functions and rules are used to assess the motor's health based on stator current values. Simulations show the motor operating normally and with introduced faults like turn-to-turn shorts and broken windings. In fault cases, the stator current becomes unbalanced and the fuzzy logic output indicates the motor health deteriorating from good to damaged or seriously damaged states.
Similar to IRJET-Condition Monitoring based Control using Piezo Sensor for Rotating Electrical Motors (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
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.