期刊
NEURAL COMPUTING & APPLICATIONS
卷 26, 期 1, 页码 187-198出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00521-014-1726-6
关键词
Fault diagnosis; Rotating machinery; Fault feature extraction; ICA with reference
资金
- Guangdong Natural Science Foundation [S2011010004143]
- Fundamental Research Funds for the Central Universities [HIT.NSRIF.2009131]
In practical situations, the vibration collected from rotating machinery is often a mixture of many vibration components and noise; therefore, it is very necessary to extract fault features from the mixture first in order to achieve effective rotating machinery fault diagnosis. In this paper, independent component analysis with reference method is proposed to extract the fault features using reference signals established based on the a priori knowledge of machine faults; experimental studies based on both simulated and actual fault signals of rotating machinery have been performed; and the results show that the proposed approach can effectively extract fault features under the situation of interferences and coexistence of multiple faults.
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