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Research on Component Failure Identification in VBE Device Circuit Boards Using Enhanced SqueezeNet Method
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Longchen LIU1, Yueping YANG1, Zhijie JIA1, Yu HUANG2, Shixiong TANG2, 3, Boyang TAN2, 3
Journal of Power Supply | 2024, 22(3) : 236 - 247
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Journal of Power Supply | 2024, 22(3): 236-247
• Reliability Analysis •
Research on Component Failure Identification in VBE Device Circuit Boards Using Enhanced SqueezeNet Method
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Longchen LIU1, Yueping YANG1, Zhijie JIA1, Yu HUANG2, Shixiong TANG2, 3, Boyang TAN2, 3
Affiliations
  • 1 Electric Power Research Institute, State Grid Sichuan Electric Power Company Chengdu 610041 China
  • 2 Ultra High Voltage DC Center, State Grid Sichuan Electric Power Company Chengdu 610000 China
  • 3 Power Internet of Things Key Laboratory of Sichuan Province Chengdu 610041 China
Published: 2024-05-30 doi: 10.13234/j.issn.2095-2805.2024.3.236
Outline
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In a direct current(DC) power transmission system, the stable operation of a valve base electronics(VBE) device is crucial for its safety. However, the traditional methods for detecting the component failures in VBE device circuit boards rely on time-consuming manual inspections or rule-based automation systems, which are often inefficient and limited in the detection accuracy. To address this problem, a method for identifying the component failure areas in VBE boards is proposed in this paper, which uses an enhanced SqueezeNet deep learning model. By incorporating depth-wise separable convolutions and residual connections, the enhanced SqueezeNet model aims to improve the accuracy of component failure detection while reducing the demand for computational resources. Experiments on a VBE board component failure dataset demonstrate that the proposed method outperforms the traditional methods and the standard SqueezeNet model in terms of detection accuracy and computational efficiency, and it achieves an accuracy rate of 95.27%, which is 4.45% higher than that of the standard model. The results of this research not only enhance the efficiency and accuracy of component failure detection in VBE boards, but also provide a novel technical reference for the diagnosis of component failures in similar equipment in power systems.

Valve base electronics (VBE) device  /  Squeeze-Net model  /  component failure detection  /  feature extraction
Longchen LIU, Yueping YANG, Zhijie JIA, Yu HUANG, Shixiong TANG, Boyang TAN. Research on Component Failure Identification in VBE Device Circuit Boards Using Enhanced SqueezeNet Method[J]. Journal of Power Supply, 2024 , 22 (3) : 236 -247 . DOI: 10.13234/j.issn.2095-2805.2024.3.236
Funding
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  • State Grid Sichuan Electric Power Company Science and Technology Project(52199723000B)
  • Sichuan Natural Science Foundation Project(2023NSFSC0818)
Appendix
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Year 2024 volume 22 Issue 3
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Article Info
doi: 10.13234/j.issn.2095-2805.2024.3.236
  • Receive Date：2024-02-03
  • Online Date：2025-07-21
  • Published：2024-05-30
Article Data
Affiliations
History
  • Received：2024-02-03
  • Revised：2024-04-22
  • Accepted：2024-05-06
Funding
State Grid Sichuan Electric Power Company Science and Technology Project(52199723000B)
Sichuan Natural Science Foundation Project(2023NSFSC0818)
Affiliations
    1 Electric Power Research Institute, State Grid Sichuan Electric Power Company Chengdu 610041 China
    2 Ultra High Voltage DC Center, State Grid Sichuan Electric Power Company Chengdu 610000 China
    3 Power Internet of Things Key Laboratory of Sichuan Province Chengdu 610041 China
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https://castjournals.cast.org.cn/joweb/dyxb/EN/10.13234/j.issn.2095-2805.2024.3.236
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