Fault Diagnosis Method of Rolling Bearing Used BP and WTA Neural Networks
LI Cheng
YU Yongbin
WANG Shunyan
XU Bin
JIN Yingtao
Abstract：This paper presents a novel pattern recognition method of fault diagnosis of rolling bearing which is based on BP and WTA neural networks.In the course of fault diagnosis, data on rolling bearing fault is transformed into desired feature vector to input to train BP-WTA, and diagnostic classification of BP and WTA neural network is obtained.By 144 experimental group samples to classify the degree of bearing damage, the diagnostic accuracy is expected to be 100% compared the BP and WTA Neural Networks with traditional method of BP and HMM, which shows that the proposed method is effective and practical in bearing fault diagnosis.
Keywords：BPWTAneural networksrolling bearingfault diagnosismemristor
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 291-298 )