Rolling bearings fault diagnosis based on adaptive Gaussian chirplet spectrogram and independent component analysis

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 工业信息学研究室 > 工业控制系统研究室

	Rolling bearings fault diagnosis based on adaptive Gaussian chirplet spectrogram and independent component analysis
	Yu HB(于海斌); Guo QJ(郭前进); Hu JT(胡静涛); Xu AD(徐皑冬)
	2006
会议名称	2nd International Conference on Natural Computation (ICNC 2006)
会议日期	September 24-28, 2006
会议地点	Xian, China
页码	321-330
通讯作者	于海斌
中文摘要	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.
收录类别	SCI ; EI ; CPCI（ISTP）
产权排序	1
会议主办者	Xidian Univ, Natl Nat Sci Fdn China, Int Neural Network Soc, Asia Pacific Neural Network Assembly, IEEE Circuits & Syst Soc, IEEE Computat Intelligence Soc, IEEE Computat Intelligence Singapore Chapter, Chinese Assoc Artificial Intelligence
会议录	ADVANCES IN NATURAL COMPUTATION, PT 1
会议录出版者	SPRINGER-VERLAG
会议录出版地	BERLIN
语种	英语
ISSN号	0302-9743
ISBN号	3-540-45901-4
WOS记录号	WOS:000241891600046
研究领域[WOS]	Computer Science
WOS标题词	Science & Technology ; Technology
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/8125]
专题	沈阳自动化研究所_工业信息学研究室_工业控制系统研究室
推荐引用方式 GB/T 7714	Yu HB,Guo QJ,Hu JT,et al. Rolling bearings fault diagnosis based on adaptive Gaussian chirplet spectrogram and independent component analysis[C]. 见:2nd International Conference on Natural Computation (ICNC 2006). Xian, China. September 24-28, 2006.