Wavelet neural network and its application in fault diagnosis of rolling bearing

Guo-Feng Wang; Tai-Yong Wang

doi:10.1117/12.664370

20 February 2006 Wavelet neural network and its application in fault diagnosis of rolling bearing

Guo-Feng Wang, Tai-Yong Wang

Proceedings Volume 6041, ICMIT 2005: Information Systems and Signal Processing; 60412B (2006) https://doi.org/10.1117/12.664370
Event: ICMIT 2005: Merchatronics, MEMS, and Smart Materials, 2005, Chongqing, China

Abstract

In order to realize diagnosis of rolling bearing of rotating machines, the wavelet neural network was proposed. This kind of artificial neural network takes wavelet function as neuron of hidden layer so as to realize nonlinear mapping between fault and symptoms. A algorithm based on minimum mean square error was given to obtain the weight value of network, dilation and translation parameter of wavelet function. To testify the correctness of wavelet neural network, it was adopted in diagnosing the fault type and location of rolling bearing. The final result shows that it can recognize the fault of outer race, inner race and roller accurately.

Citation Download Citation

Guo-Feng Wang and Tai-Yong Wang "Wavelet neural network and its application in fault diagnosis of rolling bearing", Proc. SPIE 6041, ICMIT 2005: Information Systems and Signal Processing, 60412B (20 February 2006); https://doi.org/10.1117/12.664370

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