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Shock and Vibration
Volume 2017, Article ID 6184190, 11 pages
Research Article

Rolling Bearing Reliability Assessment via Kernel Principal Component Analysis and Weibull Proportional Hazard Model

1School of Mechanical Engineering, Dalian University of Technology, Dalian, China
2School of Mathematical Sciences, Dalian University of Technology, Dalian, China
3School of Business Management, Dalian University of Technology, Dalian, China

Correspondence should be addressed to Fengtao Wang; nc.ude.tuld@tfgnaw

Received 9 December 2016; Revised 24 February 2017; Accepted 13 March 2017; Published 16 April 2017

Academic Editor: Giorgio Dalpiaz

Copyright © 2017 Fengtao Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Reliability assessment is a critical consideration in equipment engineering project. Successful reliability assessment, which is dependent on selecting features that accurately reflect performance degradation as the inputs of the assessment model, allows for the proactive maintenance of equipment. In this paper, a novel method based on kernel principal component analysis (KPCA) and Weibull proportional hazards model (WPHM) is proposed to assess the reliability of rolling bearings. A high relative feature set is constructed by selecting the effective features through extracting the time domain, frequency domain, and time-frequency domain features over the bearing’s life cycle data. The kernel principal components which can accurately reflect the performance degradation process are obtained by KPCA and then input as the covariates of WPHM to assess the reliability. An example was conducted to validate the proposed method. The differences in manufacturing, installation, and working conditions of the same type of bearings during reliability assessment are reduced after extracting relative features, which enhances the practicability and stability of the proposed method.