International Journal of Industrial Electronics and Electrical Engineering(IJIEEE).
Paper Title - Fault Detection of Induction Motor through the Analysis of Stator Current Data
The fault detection of electrical or mechanical anomalies in induction motors has been a challenging problem for
researchers over decades to ensure the safety and economic operations of industrial processes. To address this issue, this
paper studies the stator current data obtained from three phase induction motor of the healthy and faulty motor with the aim
of developing fault detection method for motor fault problems, such as bearing and broken-rotor-bar faults. Stator current
data collected from induction motors were analyzed by the principal component analysis (PCA) to obtain principal
components of statistical parameters of stator currents. The major principal components are fed as an input to feed forward
neural network for classification of faults. This paper gives the application of PCA, ANN and simplicity of the proposed
fault detection scheme for fault detection of induction motors.
Index terms - Induction Motor, Principal Component Analysis (PCA), Artificial Neural Network
Author - Anjali P. Wadekar, Anjali U. Jawadekar
Citation - Anjali P. Wadekar ,
Anjali U. Jawadekar ,
Anjali P. Wadekar, Anjali U. Jawadekar " Fault Detection of Induction Motor through the Analysis of Stator Current Data " ,
International Journal of Industrial Electronics and Electrical Engineering (IJIEEE) , Volume-5,Issue-8 ( Aug, 2017 )