Monitoring and diagnosis of bearing defects using data dependent systems

S. M. Pandit, D. Paul, J. T. Roth

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

A new bearing defect detection scheme is proposed using the dala dependent systems (DDS) methodology. The detection scheme has two parts: monitoring and diagnosis. Monitoring indicates the stability of the defect and diagnosis identifies when it is significantly large and its location. The detection scheme uses two separate indices: band energy and detection vector. Two life-tests were used to judge the effectiveness of the scheme. In both tests, the scheme identified the defect (on the inner-race and the outer-race) several days before failure occurred. The detection scheme thus provides excellent results when predicting both types of defects.

Original languageEnglish (US)
Pages (from-to)268-278
Number of pages11
JournalIntegrated Computer-Aided Engineering
Volume3
Issue number4
DOIs
StatePublished - Jan 1 1996

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Artificial Intelligence

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