Rolling bearings fault diagnosis based on adaptive gaussian chirplet spectrogram and independent component analysis
文献类型：期刊论文
| 作者 | Yu, Haibin; Guo, Qianjin; Hu, Jingtao; Xu, Aidong |
| 刊名 | Advances in natural computation, pt 1
 |
| 出版日期 | 2006 |
| 卷号 | 4221页码:321-330 |
| ISSN号 | 0302-9743 |
| 通讯作者 | Yu, haibin() |
| 英文摘要 | Condition monitoring of rolling element bearings through the use of vibration analysis is an established technique for detecting early stages of component degradation. the location dependent characteristic defect frequencies make it possible to detect the presence of a defect and to diagnose on what part of the bearing the defect is. the difficulty of localized defect detection lies in the fact that the energy of the signature of a defective bearing is spread across a wide frequency band and hence can be easily buried by noise. to solve this problem, the adaptive gaussian chirplet distribution for an integrated time-frequency signature extraction of the machine vibration is developed; the method offers the advantage of good localization of the vibration signal energy in the time-frequency domain. independent component analysis (ica) is used for the redundancy reduction and feature extraction in the time-frequency domain, and the self-organizing map (som) was employed to identify the faults of the rolling element bearings. experimental results show that the proposed method is very effective. |
| WOS关键词 | SIGNAL ; ALGORITHM ; NETWORK |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods |
| 语种 | 英语 |
| WOS记录号 | WOS:000241891600046 |
| 出版者 | SPRINGER-VERLAG BERLIN |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2379506 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Yu, Haibin |
| 作者单位 | 1.Chinese Acad Sci, Shenyang Inst Automat, Liaoning 110016, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing 100039, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Haibin,Guo, Qianjin,Hu, Jingtao,et al. Rolling bearings fault diagnosis based on adaptive gaussian chirplet spectrogram and independent component analysis[J]. Advances in natural computation, pt 1,2006,4221:321-330. |
| APA | Yu, Haibin,Guo, Qianjin,Hu, Jingtao,&Xu, Aidong.(2006).Rolling bearings fault diagnosis based on adaptive gaussian chirplet spectrogram and independent component analysis.Advances in natural computation, pt 1,4221,321-330. |
| MLA | Yu, Haibin,et al."Rolling bearings fault diagnosis based on adaptive gaussian chirplet spectrogram and independent component analysis".Advances in natural computation, pt 1 4221(2006):321-330. |
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来源：中国科学院大学
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