基于EMD复杂度特征和SVM的轴承故障诊断研究
According to the non-stationarity characteristic of the vibration signals from rolling bearing and the situation is hard to obtain enough fault samples,a comprehensive fault diagnosis method based on Empirical Mode Decomposition（EMD）,complexity measure analysis and Support Vector Machine（SVM） is pro...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2011-01-01
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| Series: | Jixie chuandong |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2011.02.019 |
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| Summary: | According to the non-stationarity characteristic of the vibration signals from rolling bearing and the situation is hard to obtain enough fault samples,a comprehensive fault diagnosis method based on Empirical Mode Decomposition（EMD）,complexity measure analysis and Support Vector Machine（SVM） is proposed.The denoised vibration signal is analyzed by using the method of EMD decomposing,and the Intrinsic Mode Functions（IMF） components are chose by using the criteria of mutual correlation coefficient between IMF components and denoised signal.The complexity of each IMF component is calculated as faulty eigenvector and served as input of SVM to recognize the fault type of rolling bearing.Practical rolling bearing experimental data diagnosis and contrast test are used to verify the effectiveness and generalization ability of this method. |
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| ISSN: | 1004-2539 |