Application of Improved Grey Wolf Optimization KFCM Algorithm in Fault Diagnosis of Wind Turbine Gearbox
In order to accurately identify the known and unknown fault types，a new fault diagnosis method for wind turbine gearbox based on the kernel fuzzy c-means clustering（KFCM）is proposed. The initially cluster centers and the kernel parameter of the KFCM model are taken as optimization variables，and an i...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2020-06-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2020.06.024 |
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| _version_ | 1841547311498395648 |
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| author | Zheng Xiaoxia Qian Yiqun Wang Shuai Zhao Kun |
| author_facet | Zheng Xiaoxia Qian Yiqun Wang Shuai Zhao Kun |
| author_sort | Zheng Xiaoxia |
| collection | DOAJ |
| description | In order to accurately identify the known and unknown fault types，a new fault diagnosis method for wind turbine gearbox based on the kernel fuzzy c-means clustering（KFCM）is proposed. The initially cluster centers and the kernel parameter of the KFCM model are taken as optimization variables，and an improved grey wolf optimization algorithm is used to find the optimal centers. The introduction of Levy flight strategy and non-linear coefficient vector in the improved grey wolf optimization algorithm can improve the convergence speed and accuracy of the algorithm， and the clustering centers and kernel parameters can be obtained under the optimal classification results. Then，according to the similarity between the new sample and the centers in the kernel space，firstly whether the sample belongs to a known fault type is determined， and then the fault type is diagnosed. Finally，the effectiveness of the proposed method is verified by experiments simulating different fault types of wind turbine gearbox. |
| format | Article |
| id | doaj-art-11c7b4b3524a4c3b91cebad4a3607513 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2020-06-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-11c7b4b3524a4c3b91cebad4a36075132025-01-10T14:45:01ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392020-06-014414214831443929Application of Improved Grey Wolf Optimization KFCM Algorithm in Fault Diagnosis of Wind Turbine GearboxZheng XiaoxiaQian YiqunWang ShuaiZhao KunIn order to accurately identify the known and unknown fault types，a new fault diagnosis method for wind turbine gearbox based on the kernel fuzzy c-means clustering（KFCM）is proposed. The initially cluster centers and the kernel parameter of the KFCM model are taken as optimization variables，and an improved grey wolf optimization algorithm is used to find the optimal centers. The introduction of Levy flight strategy and non-linear coefficient vector in the improved grey wolf optimization algorithm can improve the convergence speed and accuracy of the algorithm， and the clustering centers and kernel parameters can be obtained under the optimal classification results. Then，according to the similarity between the new sample and the centers in the kernel space，firstly whether the sample belongs to a known fault type is determined， and then the fault type is diagnosed. Finally，the effectiveness of the proposed method is verified by experiments simulating different fault types of wind turbine gearbox.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2020.06.024Grey wolf optimization |
| spellingShingle | Zheng Xiaoxia Qian Yiqun Wang Shuai Zhao Kun Application of Improved Grey Wolf Optimization KFCM Algorithm in Fault Diagnosis of Wind Turbine Gearbox Jixie chuandong Grey wolf optimization |
| title | Application of Improved Grey Wolf Optimization KFCM Algorithm in Fault Diagnosis of Wind Turbine Gearbox |
| title_full | Application of Improved Grey Wolf Optimization KFCM Algorithm in Fault Diagnosis of Wind Turbine Gearbox |
| title_fullStr | Application of Improved Grey Wolf Optimization KFCM Algorithm in Fault Diagnosis of Wind Turbine Gearbox |
| title_full_unstemmed | Application of Improved Grey Wolf Optimization KFCM Algorithm in Fault Diagnosis of Wind Turbine Gearbox |
| title_short | Application of Improved Grey Wolf Optimization KFCM Algorithm in Fault Diagnosis of Wind Turbine Gearbox |
| title_sort | application of improved grey wolf optimization kfcm algorithm in fault diagnosis of wind turbine gearbox |
| topic | Grey wolf optimization |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2020.06.024 |
| work_keys_str_mv | AT zhengxiaoxia applicationofimprovedgreywolfoptimizationkfcmalgorithminfaultdiagnosisofwindturbinegearbox AT qianyiqun applicationofimprovedgreywolfoptimizationkfcmalgorithminfaultdiagnosisofwindturbinegearbox AT wangshuai applicationofimprovedgreywolfoptimizationkfcmalgorithminfaultdiagnosisofwindturbinegearbox AT zhaokun applicationofimprovedgreywolfoptimizationkfcmalgorithminfaultdiagnosisofwindturbinegearbox |