A Fault Detection Method for Dual-output Flyback Converters Using CCA
ID：26
View Protection：PUBLIC
Updated Time：2022-12-21 10:10:06
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Poster Presentation
Start Time：Pending （Asia/Shanghai）
Duration：Pending
Session：[No Session] » [No Session Block]
Abstract
Abstract: The flyback converter is highly preferred due to their cost effectiveness and electrical isolation characteristics. Because flyback converters are so crucial to the industrial world, it is crucial to assure their continuous and secure operation. A fault detection method based on CCA is suggested to efficiently identify a fault state for dual-output flyback converters. Firstly, both outputs voltage of the dual-output flyback converter are collected and then mean-centered. CCA is used to maximize the corelationship between the dual outputs. The residual matrix was constructed according to the correlation between the two outputs obtained by CCA. Then, a statistic is used to evaluate the residual matrix. Finally, calculate the corresponding threshold. The proposed method for detecting faults focuses on the correlation between the outputs, making it possible to identify faults with minimally abnormal characteristics. Fault detection in time can avoid further losses.
Keywords
canonical correlation analysis (CCA), dual-output flyback converter, fault detection
Speaker
Cuiyu Liu
Student Harbin Institute of TechnologyCuiyu Liu received the B.S. degree from the Department of Automatic Test and Control. Harbin Institute of Technology, Harbin, China, in 2019, where she is currently pursuing the Ph.D. degree in information and communication engineering.
Her current research interests include automatic test technologies, diagnosis, and fault-tolerant con- trol approach for electronic systems.
All comments
15th August 2022 25th September 2022 - Manuscript Submission
15th October 2022 - Acceptance Notification
1st November 2022 - Camera Ready Submission
1st November 2022 10th November 2022 - Early Bird Registration
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