模拟电路故障诊断的小波方法

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Abstract A systematic method of fault diagnosis for analogue circuits based on the combination of Neural network with Wavelet Transform (WNT) is presented in the paper. Using the wavelet decomposition as a de-noise tool，the feature information is extracted by wavelet de-noise and its multi-resolution. The best fault classifier is obtained by comparing the performance of functional and weighted WNT. Diagnosis principles and steps are described. Finally, the reliability of the methods presented is shown by practical examples.

Key words： Fault diagnosis Analogue circuits Neural networks Wavelet Transform

Received: 10 January 2005

PACS:

TP206+.3

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	Tan Yang-hong
	Ye Jia-zhuo

Cite this article:

Tan Yang-hong,Ye Jia-zhuo. Wavelet Method for Fault Diagnosis of Analogue Circuits[J]. , 2006, 28(9): 1748-1751 .

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http://jeit.ie.ac.cn/EN/ OR http://jeit.ie.ac.cn/EN/Y2006/V28/I9/1748