Control of mechatronics systems: Ball bearing fault diagnosis using machine learning techniques

Hsuan Wen Peng, Pei Ju Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Ball bearing fault is one of the main causes of induction motor failure. This paper investigates in the fault diagnosis of ball bearing of three phase induction motor using random forest algorithm and C4.5 decision tree. The bearing conditions are classified to four categories: normal, bearing with inner race fault, bearing with ball fault and bearing with outer race fault. The statistical features used for classification are extracted from mechanical vibration signal in time domain and frequency domain. Principal component analysis (PCA) and linear discriminent analysis (LDA) are used to reduce the dimension and complexity of the feature set. The classification accuracy of random forest algorithm and C4.5 decision tree are analyzed and compared. The experimental results show that the random forest algorithm not only works better than the C4.5 decision tree but also can classify the ball bearing condition effectively.

Original languageEnglish
Title of host publicationASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings
Pages175-180
Number of pages6
Publication statusPublished - 2011 Aug 29
Event8th Asian Control Conference, ASCC 2011 - Kaohsiung, Taiwan
Duration: 2011 May 152011 May 18

Publication series

NameASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings

Other

Other8th Asian Control Conference, ASCC 2011
CountryTaiwan
CityKaohsiung
Period11-05-1511-05-18

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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    Peng, H. W., & Chiang, P. J. (2011). Control of mechatronics systems: Ball bearing fault diagnosis using machine learning techniques. In ASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings (pp. 175-180). [5899067] (ASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings).