Compound Fault Feature Extraction of Gearbox with Improved Local Mean Decomposition
In the case of strong noise, Ensemble local mean decomposition (ELMD) is proposed for the modal aliasing phenomenon of local mean decomposition（LMD）. However, the white noise added in ELMD cannot be completely neutralized, which will result in the reconstruction error increases due to the Product fu...
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| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2019-08-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2019.08.024 |
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| Summary: | In the case of strong noise, Ensemble local mean decomposition (ELMD) is proposed for the modal aliasing phenomenon of local mean decomposition（LMD）. However, the white noise added in ELMD cannot be completely neutralized, which will result in the reconstruction error increases due to the Product functions（PF）components to be affected by the added white noise. Therefore, a compound fault feature extraction method for gearbox based on PE-CELMD(Permutation Entropy-Complementary Ensemble local mean decomposition) is proposed. The idea is to optimize ELMD by adding pairwise white noise in combination with Permutation Entropy (PE) method based on ELMD. The method is applied to the simulated signal and the measured signal, and compared with LMD and CELMD, the results show that the PE-CELMD method is an effective compound fault feature extraction method. |
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| ISSN: | 1004-2539 |