Fault diagnosis of rolling bearing based on resonance-based sparse signal decomposition with optimal Q-factor
文献类型：期刊论文
| 作者 | Lu, Yan1; Du, Juan1; Tao, Xian2
|
| 刊名 | MEASUREMENT & CONTROL
 |
| 出版日期 | 2019-09-01 |
| 卷号 | 52期号:7-8页码:1111-1121 |
| 关键词 | Fault diagnosis resonance-based sparse signal decomposition optimal Q-factor genetic algorithm energy operator demodulating rolling bearing |
| ISSN号 | 0020-2940 |
| DOI | 10.1177/0020294019858181 |
| 通讯作者 | Lu, Yan(mly271515@163.com) |
| 英文摘要 | When a localized defect is induced, the vibration signal of rolling bearing always consists periodic impulse component accompanying with other components such as harmonic interference and noise. However, the incipient impulse component is often submerged under harmonic interference and background noise. To address the aforementioned issue, an improved method based on resonance-based sparse signal decomposition with optimal quality factor (Q-factor) is proposed in this paper. In this method, the optimal Q-factor is obtained first by genetic algorithm aiming at maximizing kurtosis value of low-resonance component of vibration signal. Then, the vibration signal is decomposed based on resonance-based sparse signal decomposition with optimal Q-factor. Finally, the low-resonance component is analyzed by empirical model decomposition combination with energy operator demodulating; the fault frequency can be achieved evidently. Simulation and application examples show that the proposed method is effective on extracting periodic impulse component from multi-component mixture vibration signal. |
| 资助项目 | National Natural Science Foundation of China[61703399] |
| WOS研究方向 | Automation & Control Systems ; Instruments & Instrumentation |
| 语种 | 英语 |
| WOS记录号 | WOS:000487111400037 |
| 出版者 | SAGE PUBLICATIONS LTD |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/26995]  |
| 专题 | 精密感知与控制研究中心_精密感知与控制 |
| 通讯作者 | Lu, Yan |
| 作者单位 | 1.Shanghai Dianji Univ, Sch Elect Engn, Shanghai 200240, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Yan,Du, Juan,Tao, Xian. Fault diagnosis of rolling bearing based on resonance-based sparse signal decomposition with optimal Q-factor[J]. MEASUREMENT & CONTROL,2019,52(7-8):1111-1121. |
| APA | Lu, Yan,Du, Juan,&Tao, Xian.(2019).Fault diagnosis of rolling bearing based on resonance-based sparse signal decomposition with optimal Q-factor.MEASUREMENT & CONTROL,52(7-8),1111-1121. |
| MLA | Lu, Yan,et al."Fault diagnosis of rolling bearing based on resonance-based sparse signal decomposition with optimal Q-factor".MEASUREMENT & CONTROL 52.7-8(2019):1111-1121. |
入库方式： OAI收割
来源：自动化研究所
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