Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning
In order to realize the unsupervised extraction and identification of fault features in power electronic circuits, we proposed a fault diagnosis method based on sparse autoencoder (SAE) and broad learning system (BLS). Firstly, the feature is extracted by the sparse autoencoder, and the fault sample...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/7463291 |
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| _version_ | 1849387165109190656 |
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| author | Ran Han Rongjie Wang Guangmiao Zeng |
| author_facet | Ran Han Rongjie Wang Guangmiao Zeng |
| author_sort | Ran Han |
| collection | DOAJ |
| description | In order to realize the unsupervised extraction and identification of fault features in power electronic circuits, we proposed a fault diagnosis method based on sparse autoencoder (SAE) and broad learning system (BLS). Firstly, the feature is extracted by the sparse autoencoder, and the fault samples and feature vectors are combined as the input of the broad learning system. The broad learning system is trained based on the error precision step update method, and the system is used to the fault type identification. The simulation results of the thyristor fault diagnosis of the three-phase bridge rectifier circuit show that the method is effective and has better performance than other traditional methods. |
| format | Article |
| id | doaj-art-3317f13fd09b49f7a39a7dba4cdbd052 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-3317f13fd09b49f7a39a7dba4cdbd0522025-08-20T03:55:17ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/74632917463291Fault Diagnosis Method of Power Electronic Converter Based on Broad LearningRan Han0Rongjie Wang1Guangmiao Zeng2Marine Engineering Institute, Jimei University, Xiamen 361021, ChinaMarine Engineering Institute, Jimei University, Xiamen 361021, ChinaMarine Engineering Institute, Jimei University, Xiamen 361021, ChinaIn order to realize the unsupervised extraction and identification of fault features in power electronic circuits, we proposed a fault diagnosis method based on sparse autoencoder (SAE) and broad learning system (BLS). Firstly, the feature is extracted by the sparse autoencoder, and the fault samples and feature vectors are combined as the input of the broad learning system. The broad learning system is trained based on the error precision step update method, and the system is used to the fault type identification. The simulation results of the thyristor fault diagnosis of the three-phase bridge rectifier circuit show that the method is effective and has better performance than other traditional methods.http://dx.doi.org/10.1155/2020/7463291 |
| spellingShingle | Ran Han Rongjie Wang Guangmiao Zeng Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning Complexity |
| title | Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning |
| title_full | Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning |
| title_fullStr | Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning |
| title_full_unstemmed | Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning |
| title_short | Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning |
| title_sort | fault diagnosis method of power electronic converter based on broad learning |
| url | http://dx.doi.org/10.1155/2020/7463291 |
| work_keys_str_mv | AT ranhan faultdiagnosismethodofpowerelectronicconverterbasedonbroadlearning AT rongjiewang faultdiagnosismethodofpowerelectronicconverterbasedonbroadlearning AT guangmiaozeng faultdiagnosismethodofpowerelectronicconverterbasedonbroadlearning |