Rolling bearing fault diagnosis based on information fusion using Dempster-Shafer evidence theory

5th Asia Conference on Mechanical and Materials Engineering

机械制造;材料科学

Pei, Di^1 ; Yue, Jianhai^1 ; Jiao, Jing^1

School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Shangyuancun, Haidian District, Beijng, China^1

关键词: Acceleration sensors;    Bearing vibrations;    Dempster-Shafer evidence theory;    Diagnostic accuracy;    Fault diagnosis method;    High speed train (HST);    Multi-sensor data;    Rolling bearings;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/241/1/012035/pdf
DOI  :  10.1088/1757-899X/241/1/012035

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

This paper presents a fault diagnosis method for rolling bearing based on information fusion. Acceleration sensors are arranged at different position to get bearing vibration data as diagnostic evidence. The Dempster-Shafer (D-S) evidence theory is used to fuse multi-sensor data to improve diagnostic accuracy. The efficiency of the proposed method is demonstrated by the high speed train transmission test bench. The results of experiment show that the proposed method in this paper improves the rolling bearing fault diagnosis accuracy compared with traditional signal analysis methods.