Fault detection in three phase induction motor using artificial intelligence

Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. In this project, the fault diagnosis of three phase induction motors is studied detailed in unbalance voltage and stator inter turn fault using simulation models and neural netw...

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Bibliographic Details
Main Author:	Unida Izwani, Md Dun
Format:	Undergraduates Project Papers
Language:	English
Published:	2010
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/2107/ http://umpir.ump.edu.my/id/eprint/2107/ http://umpir.ump.edu.my/id/eprint/2107/1/Unida_Izwani_Md_Dun_%28_CD_5332_%29.pdf

id	ump-2107
recordtype	eprints
spelling	ump-21072015-03-03T07:54:45Z http://umpir.ump.edu.my/id/eprint/2107/ Fault detection in three phase induction motor using artificial intelligence Unida Izwani, Md Dun TK Electrical engineering. Electronics Nuclear engineering Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. In this project, the fault diagnosis of three phase induction motors is studied detailed in unbalance voltage and stator inter turn fault using simulation models and neural networks have been used to train the data using Radial Basis Function Neural Network (RBFNN) in MATLAB with Graphical User Interface Development Environment (GUIDE) structured. Nowadays artificial intelligence is implemented to improve traditional techniques. The results can be obtained instantaneously after it analyzes the input data of the motor. The increased in demand has greatly improved the approach of fault detection in polyphase induction motor. Data is taken from the experiment checking the induction motor fault and is simulated into MATLAB using RBFNN. The first stage is to collect the data by experimental and simulating a Simulink model using MATLAB. Three Simulink model will be created where each of the model represent the motor condition. The result of the simulation will then be the data used to create an ANN.The second stage creates and trains an ANN. From the data obtained during the first section, a target output will determine the motor condition whether the motor is in a healthy state or fault occurred. In the third stage the development Graphical User Interface (GUI) is carried out this system. The GUI is developed by using MATLAB for the purpose of evaluating and testing the ANN. The purpose of this final year project, the development of Fault Detection in Three-Phase Induction Motor Using Artificial Intelligence is to satisfy the increased in demand to improve the approach of fault detection in polyphase induction motor. Artificial intelligence is implemented to improve traditional techniques, as the results can be obtained instantaneously after it analyzes the input data of the motor where it can be accomplished without an expert. 2010-12 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/2107/1/Unida_Izwani_Md_Dun_%28_CD_5332_%29.pdf Unida Izwani, Md Dun (2010) Fault detection in three phase induction motor using artificial intelligence. Faculty Of Electrical & Electronic Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:54960&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Unida Izwani, Md Dun Fault detection in three phase induction motor using artificial intelligence
description	Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. In this project, the fault diagnosis of three phase induction motors is studied detailed in unbalance voltage and stator inter turn fault using simulation models and neural networks have been used to train the data using Radial Basis Function Neural Network (RBFNN) in MATLAB with Graphical User Interface Development Environment (GUIDE) structured. Nowadays artificial intelligence is implemented to improve traditional techniques. The results can be obtained instantaneously after it analyzes the input data of the motor. The increased in demand has greatly improved the approach of fault detection in polyphase induction motor. Data is taken from the experiment checking the induction motor fault and is simulated into MATLAB using RBFNN. The first stage is to collect the data by experimental and simulating a Simulink model using MATLAB. Three Simulink model will be created where each of the model represent the motor condition. The result of the simulation will then be the data used to create an ANN.The second stage creates and trains an ANN. From the data obtained during the first section, a target output will determine the motor condition whether the motor is in a healthy state or fault occurred. In the third stage the development Graphical User Interface (GUI) is carried out this system. The GUI is developed by using MATLAB for the purpose of evaluating and testing the ANN. The purpose of this final year project, the development of Fault Detection in Three-Phase Induction Motor Using Artificial Intelligence is to satisfy the increased in demand to improve the approach of fault detection in polyphase induction motor. Artificial intelligence is implemented to improve traditional techniques, as the results can be obtained instantaneously after it analyzes the input data of the motor where it can be accomplished without an expert.
format	Undergraduates Project Papers
author	Unida Izwani, Md Dun
author_facet	Unida Izwani, Md Dun
author_sort	Unida Izwani, Md Dun
title	Fault detection in three phase induction motor using artificial intelligence
title_short	Fault detection in three phase induction motor using artificial intelligence
title_full	Fault detection in three phase induction motor using artificial intelligence
title_fullStr	Fault detection in three phase induction motor using artificial intelligence
title_full_unstemmed	Fault detection in three phase induction motor using artificial intelligence
title_sort	fault detection in three phase induction motor using artificial intelligence
publishDate	2010
url	http://umpir.ump.edu.my/id/eprint/2107/ http://umpir.ump.edu.my/id/eprint/2107/ http://umpir.ump.edu.my/id/eprint/2107/1/Unida_Izwani_Md_Dun_%28_CD_5332_%29.pdf
first_indexed	2023-09-18T21:55:40Z
last_indexed	2023-09-18T21:55:40Z
_version_	1777414061807370240

Fault detection in three phase induction motor using artificial intelligence

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