基于形态学滤波和EEMD方法的风力发电系统滚动轴承故障诊断
A novel method for fault diagnosis for rolling bearing of wind turbine based on combining morphological filter and ensemble empirical mode decomposition（EEMD）is presented.Firstly,de-noising processing of the practical bearing fault signal is carried out by designing open-closing and close-opening co...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2014-01-01
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| Series: | Jixie chuandong |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2014.11.020 |
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| Summary: | A novel method for fault diagnosis for rolling bearing of wind turbine based on combining morphological filter and ensemble empirical mode decomposition（EEMD）is presented.Firstly,de-noising processing of the practical bearing fault signal is carried out by designing open-closing and close-opening combined morphological filter,and then the de-noised signal is decomposed into several intrinsic mode functions（IMFs）via EEMD adaptively.The pseudo-components in EEMD are removed by using the correlation coefficient method.Finally,a more accurate Hilbert-Huang spectrum of IMFs is obtained,and the characteristic frequencies are extracted,then the fault is diagnosed.Experiment results show that the proposed method is effective for extracting fault feature. |
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| ISSN: | 1004-2539 |