An enhanced morphology gradient product filter for bearing fault detection
| Autor: | Yuejian Chen, Ming J. Zuo, Ke Feng, Yifan Li |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Signal processing
Computer science Mechanical Engineering 020208 electrical & electronic engineering ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Aerospace Engineering 02 engineering and technology Filter (signal processing) Fault (power engineering) Signal Fault detection and isolation Computer Science Applications Vibration 020303 mechanical engineering & transports 0203 mechanical engineering Control and Systems Engineering Rolling-element bearing Product (mathematics) Signal Processing 0202 electrical engineering electronic engineering information engineering Algorithm Civil and Structural Engineering |
| Zdroj: | Mechanical Systems and Signal Processing. 109:166-184 |
| ISSN: | 0888-3270 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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