Fault pattern recognition based on bispectrum entropy model

Jin Ying Huang*, Hong Xia Pan, Shi Hua Bi, Bao Zhen Cui

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

A fault pattern recognition method was developed on the basis of information entropy and bispectrum theory. The bispectrum features of vibration signal were analyzed. And a bispectrum entropy algorithm based on energy distribution was derived under the condition of subspace distribution probability. Then, the vibration signals of a gearbox under four conditions were extracted experimentally. And a BP neural network for the fault pattern recognition was established by using the bispectrum entropy feature as input. Finally, this method was verified by successfully recognizing four fault patterns of the gearbox.

Original languageEnglish
Pages (from-to)718-723
Number of pages6
JournalBinggong Xuebao/Acta Armamentarii
Volume33
Issue number6
Publication statusPublished - Jun 2012

Keywords

  • Bispectrum entropy
  • Fault
  • Feature parameter
  • Gearbox
  • Information processing
  • Pattern recognition

Fingerprint

Dive into the research topics of 'Fault pattern recognition based on bispectrum entropy model'. Together they form a unique fingerprint.

Cite this