A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network
Bearing performance degradation assessment has great significance to condition-based maintenance (CBM). A novel degradation modeling method based on EMD-SVD and fuzzy neural network (FNN) was proposed to identify and evaluate the degradation process of bearings in the whole life cycle accurately. Fi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2019/5738465 |
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| _version_ | 1832562606301249536 |
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| author | Jingbo Gai Yifan Hu Junxian Shen |
| author_facet | Jingbo Gai Yifan Hu Junxian Shen |
| author_sort | Jingbo Gai |
| collection | DOAJ |
| description | Bearing performance degradation assessment has great significance to condition-based maintenance (CBM). A novel degradation modeling method based on EMD-SVD and fuzzy neural network (FNN) was proposed to identify and evaluate the degradation process of bearings in the whole life cycle accurately. Firstly, the vibration signals of bearings in known states were decomposed by empirical mode decomposition (EMD) to obtain the intrinsic mode functions (IMFs) containing feature information. Then, the selected key IMFs which contain the main features were decomposed by singular value decomposition (SVD). And the decomposed results were used as the training samples of FNN. At last, the output results of the tested data were normalized to the health index (HI) through learning and training of FNN, and then the performance degradation degree could be described by the distance between the test sample and the normal one. According to the case study, this modeling method could evaluate the performance degradation of bearings effectively and identify the early fault features accurately. This method also provided an important maintenance strategy for the CBM of bearings. |
| format | Article |
| id | doaj-art-6504efbf3c134ef18897c94d72917251 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-6504efbf3c134ef18897c94d729172512025-02-03T01:22:17ZengWileyShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/57384655738465A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural NetworkJingbo Gai0Yifan Hu1Junxian Shen2College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, ChinaCollege of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, ChinaCollege of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, ChinaBearing performance degradation assessment has great significance to condition-based maintenance (CBM). A novel degradation modeling method based on EMD-SVD and fuzzy neural network (FNN) was proposed to identify and evaluate the degradation process of bearings in the whole life cycle accurately. Firstly, the vibration signals of bearings in known states were decomposed by empirical mode decomposition (EMD) to obtain the intrinsic mode functions (IMFs) containing feature information. Then, the selected key IMFs which contain the main features were decomposed by singular value decomposition (SVD). And the decomposed results were used as the training samples of FNN. At last, the output results of the tested data were normalized to the health index (HI) through learning and training of FNN, and then the performance degradation degree could be described by the distance between the test sample and the normal one. According to the case study, this modeling method could evaluate the performance degradation of bearings effectively and identify the early fault features accurately. This method also provided an important maintenance strategy for the CBM of bearings.http://dx.doi.org/10.1155/2019/5738465 |
| spellingShingle | Jingbo Gai Yifan Hu Junxian Shen A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network Shock and Vibration |
| title | A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network |
| title_full | A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network |
| title_fullStr | A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network |
| title_full_unstemmed | A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network |
| title_short | A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network |
| title_sort | bearing performance degradation modeling method based on emd svd and fuzzy neural network |
| url | http://dx.doi.org/10.1155/2019/5738465 |
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