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Joint time-frequency and kernel principal component based som for machine maintenance
Guo, Qianjin; Yu, Haibin; Nie, Yiyong; Xu, Aidong
刊名Advances in neural networks - isnn 2006, pt 3, proceedings
2006
卷号3973页码:1144-1154
ISSN号0302-9743
通讯作者Guo, qianjin(guoqianjin@sia.cn)
英文摘要Conventional vibration signals processing techniques are most suitable for stationary processes. however, most mechanical faults in machinery reveal themselves through transient events in vibration signals. that is, the vibration generated by industrial machines always contains nonlinear and nonstationary signals. it is expected that a desired time-frequency analysis method should have good computation efficiency, and have good resolution in both time domain and frequency domain. in this paper, the auto-regressive model based pseudo-wigner-ville distribution for an integrated time-frequency signature extraction of the machine vibration is designed, the method offers the advantage of good localization of the vibration signal energy in the time-frequency domain. kernel principal component analysis (kpca) 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 rotating machinery. experimental results show that the proposed method is very effective.
WOS关键词SIGNALS ; FAULT ; MAPS
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
语种英语
出版者SPRINGER-VERLAG BERLIN
WOS记录号WOS:000239485300167
内容类型期刊论文
URI标识http://www.corc.org.cn/handle/1471x/2379170
专题中国科学院大学
通讯作者Guo, Qianjin
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
Guo, Qianjin,Yu, Haibin,Nie, Yiyong,et al. Joint time-frequency and kernel principal component based som for machine maintenance[J]. Advances in neural networks - isnn 2006, pt 3, proceedings,2006,3973:1144-1154.
APA Guo, Qianjin,Yu, Haibin,Nie, Yiyong,&Xu, Aidong.(2006).Joint time-frequency and kernel principal component based som for machine maintenance.Advances in neural networks - isnn 2006, pt 3, proceedings,3973,1144-1154.
MLA Guo, Qianjin,et al."Joint time-frequency and kernel principal component based som for machine maintenance".Advances in neural networks - isnn 2006, pt 3, proceedings 3973(2006):1144-1154.
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