Health monitoring of rolling element bearing using a spectrum searching strategy
| Autor: | Zhencai Zhu, Qiu Mingquan, Wei Li, Bo Wu, Gongbo Zhou |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Engineering lcsh:Mechanical engineering and machinery Fast Fourier transform 02 engineering and technology Fault (power engineering) 01 natural sciences Fault detection and isolation law.invention 020901 industrial engineering & automation Search algorithm law 0103 physical sciences Frequency grid General Materials Science lcsh:TJ1-1570 010301 acoustics bearing Bearing (mechanical) business.industry Mechanical Engineering Structural engineering fault detection Line plot survey Rolling-element bearing health assessment spectrum searching business Algorithm |
| Zdroj: | Journal of Vibroengineering, Vol 19, Iss 6, Pp 4231-4246 (2017) |
| ISSN: | 2538-8460 1392-8716 |
| Popis: | Aiming at achieving early fault diagnosis and tracking the degradation process of bearings, we propose a novel monitoring methodology using a spectrum searching strategy in this paper. Firstly, a vibration signal is collected with appropriate sampling frequency and length. Secondly, the structural information of spectrum (SIOS) on a predefined frequency grid is constructed through a searching algorithm after deriving the single-sided FFT spectrum. Finally, the two-dimensional (2-D) line plot of the frequency grid versus the average power in SIOS is employed to conduct fault detection and the sum of the largest six total-power (SLSTP) of the frequency grid in SIOS is calculated as a health indication to demonstrate the changes in the bearing’s health status. The performance of the proposed scheme is validated with both simulation and bearing data. Experimental results show that the monitoring algorithm could manifest satisfactory behaviors in early fault diagnosis and health assessment of bearings. |
| Databáze: | OpenAIRE |
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