Rolling element bearing fault diagnostics

Development of health index

H. S. Kumar, Srinivasa P. Pai, N. S. Sriram, G. S. Vijay

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This article develops and compares health indices using different approaches namely singular value decomposition, average value of the cumulative feature and Mahalanobis distance for assessing the rolling element bearing condition. The vibration signals for four conditions of rolling element bearing are acquired from a customized bearing test rig under variable load conditions. Seventeen statistical features are extracted from wavelet coefficients of the denoised signals. Feature selection is performed using singular value decomposition and kernel Fisher discriminant analysis. These selected features are used in these three approaches to develop health indices. Finally, a comparison of the three proposed approaches is made to select the best approach which can be effectively used for fault diagnosis of rolling element bearings.

Original languageEnglish
Pages (from-to)3923-3939
Number of pages17
JournalProceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
Volume231
Issue number21
DOIs
Publication statusPublished - 01-11-2017

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Bearings (structural)
Health
Singular value decomposition
Discriminant analysis
Failure analysis
Feature extraction

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

Cite this

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Rolling element bearing fault diagnostics : Development of health index. / Kumar, H. S.; Pai, Srinivasa P.; Sriram, N. S.; Vijay, G. S.

In: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol. 231, No. 21, 01.11.2017, p. 3923-3939.

Research output: Contribution to journalArticle

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