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Diagnosis of Incipient Faults in Weak Nonlinear Analog Circuits

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Abstract

Aiming at the problem to diagnose incipient faults in weak nonlinear analog circuits, an approach is presented in this paper. The approach calculates the fractional Volterra correlation functions beforehand. The next step is to use the fractional Volterra correlation functions and different angle parameters of the fractional wavelet packet transform (FRWPT) to extract the fault signatures. Meanwhile, the computational complexity is analyzed. Then the variables of the fault signatures are constructed, which are used to form the observation sequences of the hidden Markov model (HMM). HMM is used to accomplish the fault diagnosis. The simulations show that the presented method can significantly improve the incipient fault diagnosis capability.

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Acknowledgements

The authors would like to thank the reviewers and the editors for their constructive comments and suggestions.

This work is supported by Program for New Century Excellent Talents in University (NCET-05-0804) and partly supported by Chinese National Programs for High Technology Research and Development (2006AA06Z222).

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Authors and Affiliations

  1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Yibing Shi, Yong Deng & Wei Zhang

  2. School of Electronics and Information Engineering, Southwest Petroleum University, Chengdu, 610500, China

    Yong Deng

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  1. Yibing Shi
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  2. Yong Deng
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  3. Wei Zhang
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Correspondence to Yong Deng.

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Shi, Y., Deng, Y. & Zhang, W. Diagnosis of Incipient Faults in Weak Nonlinear Analog Circuits. Circuits Syst Signal Process 32, 2151–2170 (2013). https://doi.org/10.1007/s00034-013-9589-0

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  • DOI: https://doi.org/10.1007/s00034-013-9589-0

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