A One-Versus-All Class Binarization Strategy for Bearing Diagnostics of Concurrent Defects

A One-Versus-All Class Binarization Strategy for Bearing Diagnostics of Concurrent Defects

In bearing diagnostics using a data-driven modeling approach, a concern is the need for data from all possible scenarios to build a practical model for all operating conditions. This paper is a study on bearing diagnostics with the concurrent occurrence of multiple defect types. The authors are not...

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Bibliographic Details
Main Authors: Selina S. Y. Ng, Peter W. Tse, Kwok L. Tsui
Format: Article
Language:English
Published: MDPI AG 2014-01-01
Series:Sensors
Subjects:
bearing
multiple defects
fault diagnostics
class binarization
support vector machine (SVM)
decision tree
Online Access:http://www.mdpi.com/1424-8220/14/1/1295

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