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Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning
Joint Authors
Han, Ran
Wang, Rongjie
Zeng, Guangmiao
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-09
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Han, Ran& Wang, Rongjie& Zeng, Guangmiao. 2020. Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning. Complexity،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1143743
Modern Language Association (MLA)
Han, Ran…[et al.]. Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning. Complexity No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1143743
American Medical Association (AMA)
Han, Ran& Wang, Rongjie& Zeng, Guangmiao. Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning. Complexity. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1143743
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143743