Optimal Feature Set for Detection of Inner Race Defect in Rolling Element Bearings

Karthik Kappaganthu, C. Nataraj, and Biswanath Samanta
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_09_76.pdf486.69 KBSeptember 15, 2009 - 3:34pm

Rolling element bearings are key components in most rotating machinery. It is necessary to determine the condition of the bearing with reasonable degree of confidence. Many techniques have been developed for bearing fault detection. Each of these techniques have their own strengths and weaknesses. In this paper various features are compared for detecting inner race defects in rolling element bearings. Mutual information between the feature and defect is used as a quantitative measure of quality and the features are ranked appropriately. Often, a combination of different features is used for bearing fault detection. Hence it is important to understand the interaction of features for classification purposes. This paper addresses this issue and determines the optimal feature set for best detection performance.

Publication Control Number: 
076
Submission Keywords: 
bearings
damage detection
damage modeling
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