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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.<\/jats:p>","DOI":"10.1155\/2020\/7463291","type":"journal-article","created":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T23:54:51Z","timestamp":1594338891000},"page":"1-9","source":"Crossref","is-referenced-by-count":6,"title":["Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning"],"prefix":"10.1155","volume":"2020","author":[{"given":"Ran","family":"Han","sequence":"first","affiliation":[{"name":"Marine Engineering Institute, Jimei University, Xiamen 361021, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9994-820X","authenticated-orcid":true,"given":"Rongjie","family":"Wang","sequence":"additional","affiliation":[{"name":"Marine Engineering Institute, Jimei University, Xiamen 361021, China"},{"name":"Fujian Provincial Key Laboratory of Naval Architecture and 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