Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis
In industrial production, it is highly essential to extract faults in gearbox accurately. Specifically, in a strong noise environment, it is difficult to extract the fault features accurately. LMD (local mean decomposition) is widely used as an adaptive decomposition method in fault diagnosis. In or...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/1564243 |
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| author | Zhijian Wang Junyuan Wang Wenan Cai Jie Zhou Wenhua Du Jingtai Wang Gaofeng He Huihui He |
| author_facet | Zhijian Wang Junyuan Wang Wenan Cai Jie Zhou Wenhua Du Jingtai Wang Gaofeng He Huihui He |
| author_sort | Zhijian Wang |
| collection | DOAJ |
| description | In industrial production, it is highly essential to extract faults in gearbox accurately. Specifically, in a strong noise environment, it is difficult to extract the fault features accurately. LMD (local mean decomposition) is widely used as an adaptive decomposition method in fault diagnosis. In order to improve the mode mixing of LMD, ELMD (ensemble Local Mean Decomposition) is proposed as local mode mixing exists in noisy environment, but white noise added in ELMD cannot be completely neutralized leading to the influence of increased white noise on PF (product function) component. This further leads to the increase in reconstruction errors. Therefore, this paper proposes a composite fault diagnosis method for gearboxes based on an improved ensemble local mean decomposition. The idea is to add white noise in pairs to optimize ELMD, defined as CELMD (Complementary Ensemble Local Mean Decomposition) then remove the decomposed high noise component by PE (Permutation Entropy) while applying the SG (Savitzky-Golay) filter to smooth out the low noise in PFs. The method is applied to both simulated signal and experimental signal, which overcomes mode mixing phenomenon and reduces reconstruction error. At the same time, this method avoids the occurrence of pseudocomponents and reduces the amount of calculation. Compared with LMD, ELMD, CELMD, and CELMDAN, it shows that improved ensemble local mean decomposition method is an effective method for extracting composite fault features. |
| format | Article |
| id | doaj-art-44b835af037845749697e56540ea6389 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-44b835af037845749697e56540ea63892025-02-03T01:21:07ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/15642431564243Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault DiagnosisZhijian Wang0Junyuan Wang1Wenan Cai2Jie Zhou3Wenhua Du4Jingtai Wang5Gaofeng He6Huihui He7School of Mechanical Engineering, North University of China, Taiyuan, Shanxi 030051, ChinaSchool of Mechanical Engineering, North University of China, Taiyuan, Shanxi 030051, ChinaSchool of Mechanical Engineering, Jinzhong University, Jinzhong, Shanxi 030600, ChinaSchool of Mechanical Engineering, North University of China, Taiyuan, Shanxi 030051, ChinaSchool of Mechanical Engineering, North University of China, Taiyuan, Shanxi 030051, ChinaSchool of Mechanical Engineering, North University of China, Taiyuan, Shanxi 030051, ChinaSchool of Mechanical Engineering, North University of China, Taiyuan, Shanxi 030051, ChinaSchool of Mechanical Engineering, North University of China, Taiyuan, Shanxi 030051, ChinaIn industrial production, it is highly essential to extract faults in gearbox accurately. Specifically, in a strong noise environment, it is difficult to extract the fault features accurately. LMD (local mean decomposition) is widely used as an adaptive decomposition method in fault diagnosis. In order to improve the mode mixing of LMD, ELMD (ensemble Local Mean Decomposition) is proposed as local mode mixing exists in noisy environment, but white noise added in ELMD cannot be completely neutralized leading to the influence of increased white noise on PF (product function) component. This further leads to the increase in reconstruction errors. Therefore, this paper proposes a composite fault diagnosis method for gearboxes based on an improved ensemble local mean decomposition. The idea is to add white noise in pairs to optimize ELMD, defined as CELMD (Complementary Ensemble Local Mean Decomposition) then remove the decomposed high noise component by PE (Permutation Entropy) while applying the SG (Savitzky-Golay) filter to smooth out the low noise in PFs. The method is applied to both simulated signal and experimental signal, which overcomes mode mixing phenomenon and reduces reconstruction error. At the same time, this method avoids the occurrence of pseudocomponents and reduces the amount of calculation. Compared with LMD, ELMD, CELMD, and CELMDAN, it shows that improved ensemble local mean decomposition method is an effective method for extracting composite fault features.http://dx.doi.org/10.1155/2019/1564243 |
| spellingShingle | Zhijian Wang Junyuan Wang Wenan Cai Jie Zhou Wenhua Du Jingtai Wang Gaofeng He Huihui He Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis Complexity |
| title | Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis |
| title_full | Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis |
| title_fullStr | Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis |
| title_full_unstemmed | Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis |
| title_short | Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis |
| title_sort | application of an improved ensemble local mean decomposition method for gearbox composite fault diagnosis |
| url | http://dx.doi.org/10.1155/2019/1564243 |
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