Fault diagnosis and prognosis using wavelet packet decomposition, Fourier transform and artificial neural network

2012 ◽  
Vol 24 (6) ◽  
pp. 1213-1227 ◽  
Author(s):  
Zhenyou Zhang ◽  
Yi Wang ◽  
Kesheng Wang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fourier Transform ◽  
Fault Diagnosis ◽  
Wavelet Packet ◽  
Wavelet Packet Decomposition ◽  
Diagnosis And Prognosis ◽  
Artificial Neural ◽  
Fault Diagnosis And Prognosis

Application of Wavelet Packet Transform for Detection of Ball Bearing Race Fault

2009 ◽  
Vol 626-627 ◽  
pp. 511-516
Author(s):  
Dong Yun Wang ◽  
Wen Zhi Zhang ◽  
Wei Ping Lu ◽  
J.W. Du
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fault Diagnosis ◽  
Ball Bearing ◽  
Wavelet Packet ◽  
Vibration Signal ◽  
Wavelet Packet Transform ◽  
Rolling Ball ◽  
Bearing Race ◽  
Artificial Neural

In this study, a fault diagnosis system is proposed for rolling ball bearing race using wavelet packet transform(WPT) and artificial neural network(ANN)technique. Vibration signal from ball bearings having defects on inner race and outer race is considered and the extraction method of feature vector based on wavelet packet transform with frequency band energy is used. The vibration signal is decomposed into the individual frequency bands. The variations of the signal energy in these bands reflect the different fault locations. Further, the artificial neural network is proposed to develop the diagnostic rules of the data base in the present fault identification system. The experimental work is performed to evaluate the effect of fault diagnosis in a rolling ball bearing platform under different fault conditions. The experimental results indicate the effectiveness of the proposed method in fault bearing identification.

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