Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM
Misalignment is an important cause for the early failure of large doubly-fed wind turbines (DFWT). For the non-stationary characteristics of the signals in the transmission system of DFWT and the reality that it is difficult to obtain a large number of fault samples, Solidworks and Adams are used to...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-01-01
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| Series: | Entropy |
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| Online Access: | http://www.mdpi.com/1099-4300/19/1/6 |
| _version_ | 1818008390732873728 |
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| author | Yancai Xiao Na Kang Yi Hong Guangjian Zhang |
| author_facet | Yancai Xiao Na Kang Yi Hong Guangjian Zhang |
| author_sort | Yancai Xiao |
| collection | DOAJ |
| description | Misalignment is an important cause for the early failure of large doubly-fed wind turbines (DFWT). For the non-stationary characteristics of the signals in the transmission system of DFWT and the reality that it is difficult to obtain a large number of fault samples, Solidworks and Adams are used to simulate the different operating conditions of the transmission system of the DFWT to obtain the corresponding characteristic signals. Improved empirical mode decomposition (IEMD), which improves the end effects of empirical mode decomposition (EMD) is used to decompose the signals to get intrinsic mode function (IMF), and the IEMD energy entropy reflecting the working state are extracted as the inputs of the support vector machine (SVM). Particle swarm optimization (PSO) is used to optimize the parameters of SVM to improve the classification performance. The results show that the proposed method can effectively and accurately identify the types of misalignment of the DFWT. |
| first_indexed | 2024-04-14T05:28:41Z |
| format | Article |
| id | doaj.art-dbdd664df43c4aad95eb5f655333c54f |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-14T05:28:41Z |
| publishDate | 2017-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-dbdd664df43c4aad95eb5f655333c54f2022-12-22T02:09:53ZengMDPI AGEntropy1099-43002017-01-01191610.3390/e19010006e19010006Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVMYancai Xiao0Na Kang1Yi Hong2Guangjian Zhang3School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaMisalignment is an important cause for the early failure of large doubly-fed wind turbines (DFWT). For the non-stationary characteristics of the signals in the transmission system of DFWT and the reality that it is difficult to obtain a large number of fault samples, Solidworks and Adams are used to simulate the different operating conditions of the transmission system of the DFWT to obtain the corresponding characteristic signals. Improved empirical mode decomposition (IEMD), which improves the end effects of empirical mode decomposition (EMD) is used to decompose the signals to get intrinsic mode function (IMF), and the IEMD energy entropy reflecting the working state are extracted as the inputs of the support vector machine (SVM). Particle swarm optimization (PSO) is used to optimize the parameters of SVM to improve the classification performance. The results show that the proposed method can effectively and accurately identify the types of misalignment of the DFWT.http://www.mdpi.com/1099-4300/19/1/6misalignmentDFWTIEMD energy entropyPSOSVM |
| spellingShingle | Yancai Xiao Na Kang Yi Hong Guangjian Zhang Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM Entropy misalignment DFWT IEMD energy entropy PSO SVM |
| title | Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM |
| title_full | Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM |
| title_fullStr | Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM |
| title_full_unstemmed | Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM |
| title_short | Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM |
| title_sort | misalignment fault diagnosis of dfwt based on iemd energy entropy and pso svm |
| topic | misalignment DFWT IEMD energy entropy PSO SVM |
| url | http://www.mdpi.com/1099-4300/19/1/6 |
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