基于波形相似度的容差模拟电路软故障诊断

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Abstract Regarding to the random attribute of the parameters of tolerance analog circuit output waveform, the feature interval vector used to describe the tolerance analog circuit in a certain mode is constructed. Accordingly, a novel soft fault diagnosis method based on waveform similarity acquired by multi-frequency tests is proposed. For each fault mode of the circuit under test, K standard feature interval vectors are acquired by K tests with alternating current signal inputs with different frequencies respectively. In order to diagnose the fault mode of the circuit, it is input with the same signals with K different frequencies to form K output wave parameter samples. K wave similarities are calculated by the K output wave parameter samples with the K standard feature interval vectors of each fault mode. The integrated similarity is the fusion of the K wave similarities considering mean square deviation weight and credibility weight. Finally, fault location is realized by a set of fuzzy rules. The simulation results show that the proposed method gains satisfactory accuracy while less limited by accessible test points. Moreover, it is practical and easy to be realized in automatic test systems.

Key words： Analog circuit fault diagnosis feature interval vector multi-frequency test waveform similarity

Received: 27 January 2011 Published: 20 March 2014

PACS:

TP206+.3

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	Zhong Jianlin
	He You
	Ren Xianbin

Cite this article:

Zhong Jianlin,He You,Ren Xianbin. Soft Fault Diagnosis Based on Waveform Similarity for Tolerance Analog Circuit[J]. Transactions of China Electrotechnical Society, 2012, 27(8): 222-229.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2012/V27/I8/222

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