Rolling element bearing fault diagnostics: Development of health index

Kumar, HS and Pai, Srinivasa P and Sriram, N S and Vijay, G S (2018) Rolling element bearing fault diagnostics: Development of health index. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 231 (21). pp. 3923-3939. ISSN 0954-4062

[img] PDF
3976.pdf - Published Version
Restricted to Registered users only

Download (1MB) | Request a copy

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.

Item Type: Article
Uncontrolled Keywords: Feature extraction, singular value decomposition, cumulative feature, Mahalanobis distance, health index
Subjects: Engineering > MIT Manipal > Mechanical and Manufacturing
Depositing User: MIT Library
Date Deposited: 14 Feb 2018 09:18
Last Modified: 14 Feb 2018 09:18
URI: http://eprints.manipal.edu/id/eprint/150576

Actions (login required)

View Item View Item