Research of confidence rule base for fault diagnosis of rolling bearing based on faulty sample

Authors

Hong QIAN, School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090 ,China；Shanghai Power Station automation technology key laboratory, Shanghai 200072 ,China
Zibin ZHENG, School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090 ,China
Yuqing FENG, School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090 ,China

Keywords

rolling bearing, Feature fusion, characteristic parameter, fault diagnosis, confidence rule base

Abstract

The rolling bearing is a widely used mechanical part, but the existing technology has limitations on the fault diagnosis of rolling bearing. In order to improve the accuracy of rolling bearing fault diagnosis, a method of confidence rule base is proposed on the basis of fault samples by using historical data. Firstly, the typical faults of rolling bearing are analyzed, and their vibration data are obtained as samples to extract. The timedomain and timefrequency parameters are then fused and symptom parameters are extracted to build the confidence rule base of fault diagnosis. Finally, the abnormal data of rolling bearing are obtained through the experimental platform, which verifies the validity and accuracy of the established confidence rule base.

DOI

10.19781/j.issn.16739140.2020.01.019

First Page

144

Last Page

150

Recommended Citation

QIAN, Hong; ZHENG, Zibin; and FENG, Yuqing (2020) "Research of confidence rule base for fault diagnosis of rolling bearing based on faulty sample," Journal of Electric Power Science and Technology: Vol. 35: Iss. 1, Article 19.
DOI: 10.19781/j.issn.16739140.2020.01.019
Available at: https://jepst.researchcommons.org/journal/vol35/iss1/19