Optimal feature set for detection of inner race defect in rolling element bearings

Karthik Kappaganthu, C. Nataraj, Biswanath Samanta

Research output: Contribution to book or proceedingConference articlepeer-review

3 Scopus citations

Abstract

Rolling element bearings are the key components in many 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.

Original languageEnglish
Title of host publicationAnnual Conference of the Prognostics and Health Management Society, PHM 2009
PublisherPrognostics and Health Management Society
ISBN (Electronic)9781936263004
StatePublished - 2009
EventAnnual Conference of the Prognostics and Health Management Society, PHM 2009 - San Diego, United States
Duration: Sep 27 2009Oct 1 2009

Publication series

NameAnnual Conference of the Prognostics and Health Management Society, PHM 2009

Conference

ConferenceAnnual Conference of the Prognostics and Health Management Society, PHM 2009
Country/TerritoryUnited States
CitySan Diego
Period09/27/0910/1/09

Scopus Subject Areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Software
  • Health Information Management

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