Adaptive BP Wavelet Neural Network Method for Soft Fault Diagnosis in Analog Circuit

Wei Cong; Bo Jing; Hong Kun Yu

doi:10.4028/www.scientific.net/AMM.307.327

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 307Adaptive BP Wavelet Neural Network Method for Soft...

Adaptive BP Wavelet Neural Network Method for Soft Fault Diagnosis in Analog Circuit

Abstract:

Because of the diversity and complexity of soft fault in analog circuit, the rapid and accurate diagnosis is very difficult. For this, an adaptive BP wavelet neural network diagnosis method of soft fault is proposed. It combines the time-frequency localization characteristics of wavelet and the self-learning ability of neural network in soft fault diagnosis of analog circuit, and by introducing the adaptive learning rate the diagnosis ability of BP wavelet neural network model can effectively be improved. In addition, PSPICE software is used to obtain the simulation data of actual analog circuit for the experiment. The results also verify the validity of the proposed method.

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Periodical:

Applied Mechanics and Materials (Volume 307)

Pages:

327-330

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.307.327

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Online since:

February 2013

Authors:

Wei Cong, Bo Jing, Hong Kun Yu

Keywords:

Adaptive Learning Rate, BP Algorithm, Soft Fault Diagnosis, Wavelet Neural Network (WNN)

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