Monitoring and Diagnosis of Bearing Defects Using Data Dependent Systems

Issue title: Faults in Automated Manufacturing

Guest editors: Maria GiniGuest Editor

Article type: Research Article

Authors: Pandit, S.M.^{; *} | Paul, D. | Roth, J.T.

Affiliations: Mechanical Engineering-Engineering Mechanics Department, Michigan Technological University, Houghton, MI 49931

Correspondence: [*] Author to whom all correspondence should be addressed.

Abstract: A new bearing defect detection scheme is proposed using the data 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.

DOI: 10.3233/ICA-1996-3404

Journal: Integrated Computer-Aided Engineering, vol. 3, no. 4, pp. 268-278, 1996