An adaptive fault detection method based on atom sparse and evidence fusion for the small current to ground system

  • Xiaowei Wang
  • , Xiangxiang Wei
  • , Dechang Yang
  • , Jie Gao
  • , Xue Sun
  • , Guobing Song

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

An adaptive fault detection method for the small current to ground system is proposed based on the atom sparse and evidence fusion theory. Firstly, the two cycles of transient zero-sequence current are obtained when occur fault, which is decomposed by the matching pursuit algorithm, and the iterations are set to four, then, according to the correlation analysis, the best three atoms of maximum correlation are chosen and which are sorted by the correlation coefficients. Secondly, we obtained the determine fault measure (DFM) values by calculating the atomic energy entropy, and selected the atomic fault trust (FT) function by revising the DFM. Finally, the FT values are integrated by the D-S (Dempster–Shafer) evidence theory, then the fault comprehensive trust values are gained, the selection results are output. Simulation results show that the method of fault line detection is accurate and reliable.

Original languageEnglish
Pages (from-to)1579-1592
Number of pages14
JournalTransactions of the Institute of Measurement and Control
Volume40
Issue number5
DOIs
StatePublished - 1 Mar 2018

Keywords

  • D-S evidence theory
  • Fault detection
  • correlation analysis
  • energy entropy
  • fault trust function
  • matching pursuit algorithm

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