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Rolling bearing health status assessment based on ITD-GMM method

  • Haitao Lu
  • , Zili Wang*
  • *Corresponding author for this work
  • Beihang University
  • Science & Technology on Reliability & Environmental Engineering Laboratory

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper proposed a Rolling bearing health state assessment based on ITD-GMM method to fully dig the favorable information of the vibration signal from the rolling bearing with decline trend. By data analytic, the six components of vibration signal were calculated, and each component has three feature vectors. Finally, the performance of rolling bearing was quantified, and the curve of performance was acquired. The experimental results indicate that the method is feasible and effective for the assessment of rolling bearing.

Original languageEnglish
Pages (from-to)46-50
Number of pages5
JournalVibroengineering Procedia
Volume16
DOIs
StatePublished - 1 Dec 2017
Externally publishedYes
Event30th International Conference on Vibroengineering - Phuket, Thailand
Duration: 16 Dec 201717 Dec 2017

Keywords

  • Gaussian mixture model
  • Health state assessment
  • Intrinsic time-scale decomposition
  • Rolling bearing

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