학술논문
Identification of broken rotor bar fault and degree of loading in induction motor using neuro-wavelets
Document Type
Conference
Author
Source
TENCON 2015 - 2015 IEEE Region 10 Conference. :1-5 Nov, 2015
Subject
Language
ISSN
2159-3442
2159-3450
2159-3450
Abstract
This paper presents a methodology for the detection of broken rotor bar fault in induction motor at different load conditions. Wavelet transform is applied to the stator current, for the extraction of the signature of the fault. These wavelet coefficients are fed as input to a feedforward neural network. The output of the neural network classifies the health of the rotor of the induction motor (healthy/ faulty), and also the load at which the machine is operating. The entire simulation is carried out using MATLAB. The proposed network has performance efficiency of 93.75%.