3-phase induction motor fault diagnosis based on artificial neural network
Dissertant
Thesis advisor
Mahmud, Dari Yusuf
Abd al-Baqi, Isam M.
University
University of Technology
Faculty
-
Department
Department of Electromechanical Engineering
University Country
Iraq
Degree
Ph.D.
Degree Date
2010
English Abstract
This work presents a practical study associated with theoretical analysis and computer simulation of different faults of certain three phase induction motor.
It also includes the diagnoses of these faults by using Motor Current Signature Analysis (MCSA) Technique Associated with neural network algorithm.
Mathematical models for healthy and faulty conditions had been built to demonstrate theoretically the behavior of 3-phase induction motor.
Simulation results are presented from the model implemented in the MATLAB / Simulink.
MCSA focuses on the spectral analysis of stator current.
In this study, the magnitudes of the generated upper and lower harmonics in the spectrum of faulty currents are determined experimentally as a function of load torque for each fault by using practical data acquisition and a Fast Fourier Transform (FFT) analysis of the currents.
It is found that the behaviors of current harmonics of each fault are widely different from that of other faults.
An Artificial Neural Network (ANN) technique for the detection of five major induction motor faults has been experimentally tested for the above diagnosis techniques.
The three fault conditions including broken rotor bar, bearing fault, and inter turn faults of three phase squirrel cage induction motors type (2.2 kW, 3000 rpm) are considered.
The harmonic content for each faulty motor current, through the loading range are fed to neural network algorithm.
A numerical optimization technique using Liebenberg-Marquardt algorithm has been done for ANN training and testing.
Main Subjects
Topics
American Psychological Association (APA)
Husayn, Nawal Ali. (2010). 3-phase induction motor fault diagnosis based on artificial neural network. (Doctoral dissertations Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305044
Modern Language Association (MLA)
Husayn, Nawal Ali. 3-phase induction motor fault diagnosis based on artificial neural network. (Doctoral dissertations Theses and Dissertations Master). University of Technology. (2010).
https://search.emarefa.net/detail/BIM-305044
American Medical Association (AMA)
Husayn, Nawal Ali. (2010). 3-phase induction motor fault diagnosis based on artificial neural network. (Doctoral dissertations Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305044
Language
English
Data Type
Arab Theses
Record ID
BIM-305044
