Title of Paper:Rolling Bearing Reliability Estimation Based on Logistic Regression Model

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Date of Publication:2013-01-01

Included Journals:CPCI-S、Scopus

Page Number:1730-1733

Key Words:rolling bearing; reliability estimation; logistic regression model; vibration; feature extraction

Abstract:Rolling bearing (RB) has been broadly applied on mechanical systems. Its reliability is directly related to the performance of the whole mechanical system. RB reliability estimation technology is crucial for mechanical system. Logistic regression model (LRM) is constructed for RB reliability estimation in this paper. Vibration data acquisition and feature extraction are carried on for. Based on feature extraction investigation, root mean square and wavelet entropy are used to construct characteristics vector. Therefore, bearing degradation state information is determined by vibration information. Reliability estimation model based on LRM is constructed to estimate bearing performance. By using LRM, it has good performance on reliability estimation. It can be concluded that LRM is beneficial for RB life prediction.