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Power Electronic Circuit Fault Diagnosis Method Based on GADF and Channel Split Residual Network
  • Yuanyuan Jiang,
  • Jinyang Xie
Yuanyuan Jiang
Anhui University of Science and Technology

Corresponding Author:[email protected]

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Jinyang Xie
Anhui University of Science and Technology
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Power electronic circuits play an extremely important role in industrial systems. Parametric failure of components in these circuits are extremely prone to occur, which can easily evolve into catastrophic failures with time. Hence fault diagnosis of circuits can avoid catastrophic failures. In this paper, we propose a channel segmentation residual network (CSRN) for circuit fault diagnosis, in which Gram angular difference filed (GADF) is used to convert the original fault signal into a two-dimensional feature map for input into the CSRN. The channels of the input feature map are distinguished by selecting the main working channels through a channel segmentation mechanism and a Darwin selection mechanism for feature retention and deletion operations. The diagnostic performance of the proposed method is verified on the DC-DC circuit fault dataset, and the results show that the proposed CSRN achieves 97.92% fault classification accuracy for this circuit, which is 1.98%, 13.34% and 6.67% higher than other models, respectively.
17 Nov 2022Submitted to International Journal of Circuit Theory and Applications
18 Nov 2022Review(s) Completed, Editorial Evaluation Pending
18 Nov 2022Submission Checks Completed
18 Nov 2022Assigned to Editor
19 Nov 2022Reviewer(s) Assigned
15 Dec 2022Editorial Decision: Revise Major
20 Feb 20231st Revision Received
06 Mar 2023Submission Checks Completed
06 Mar 2023Assigned to Editor
06 Mar 2023Review(s) Completed, Editorial Evaluation Pending
06 Mar 2023Reviewer(s) Assigned
16 Apr 2023Editorial Decision: Revise Minor