Detection and Diagnosis of Induction Motor Faults by Intelligent Techniques

  • Riyah Najim Kiter, Ass. Prof. Dr. Engineering College -Al-Anbar University
  • Mohammed Moanes Ezzaldean, Lecturer Department of Electrical Engineering – University of Technology
  • Yousif Ismail Almashhdany, Ass. Prof. Dr. Engineering College -Al-Anbar University
  • Fuad Lateef Salim, Lecturer Engineering College -Al-Anbar University
Keywords: induction motor, faults detection, diagnosis, intelligent system.

Abstract

This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosis system is developed to determine the status of the motor without the need for an expert. This system is based on artificial neural network (ANN) and it is characterized by speed and accuracy and the ability to detect more than one fault at the same time.
 

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Published
2017-01-01
How to Cite
Kiter, R., Ezzaldean, M., Almashhdany, Y. and Salim, F. (2017) “Detection and Diagnosis of Induction Motor Faults by Intelligent Techniques”, Journal of Engineering, 23(1), pp. 29-47. Available at: http://joe.uobaghdad.edu.iq/index.php/main/article/view/94 (Accessed: 19September2020).