Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6954102 | Mechanical Systems and Signal Processing | 2018 | 19 Pages |
Abstract
This paper presents a signal processing scheme, namely enhanced morphology gradient product filter (EMGPF), for rolling element bearing fault detection. In this scheme, a morphology gradient product operation (MGPO) is firstly proposed to extract impulsive features of a raw signal according to a comprehensive investigation of the working mechanism of the reported morphological operations. Then, a higher-order spectrum analysis method, the third-order cumulant slice spectrum, is used to improve the performance of the MGPO based morphology filter for the purpose of highlighting fault features further. Experimental vibration signals were employed to evaluate the effectiveness of the proposed EMGPF. Results show that the proposed method has a superior performance in extracting fault features of defective rolling element bearing over four reported morphology filters.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Yifan Li, Ming J. Zuo, Yuejian Chen, Ke Feng,