Analog circuit fault diagnosis based on locality preserving projection and hidden markov model

Xiang Qian Li, Shi Kai Jing*, Yan Yan, Hai Cheng Yang, Jing Tao Zhou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Aiming at the non-linear characteristics of analog circuit, a fault diagnosis method of analog circuit based on locality preserving projection (LPP) and hidden Markov model (HMM) was presented. Firstly, the high-dimensional space was constructed by extracting the signal characteristics of analog circuit. Secondly, the LPP was used to compress the feature samples and the intrinsic manifold feature in data set was extracted as characteristic vector. Finally, the classification and recognition of all status were implemented with HMM constructed for reflecting the real status of the system. Simulation analysis results show that, compared with other methods, the LPP-HMM can effectively identify incipient faults, and possess higher rate of fault identification.

Original languageEnglish
Pages (from-to)919-923 and 960
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume35
Issue number9
DOIs
Publication statusPublished - 1 Sept 2015

Keywords

  • Analog circuit
  • Fault diagnosis
  • Hidden Markov model (HMM)
  • Locality preserving projection

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