Research on detection method of over-current fault point of transmission cable ring network based on fault tree

Junpeng Dang; Jinhai Yang; Xuefeng Liu; Lei Yu; Ying Lin

doi:10.1117/12.2671351

28 April 2023 Research on detection method of over-current fault point of transmission cable ring network based on fault tree

Junpeng Dang, Jinhai Yang, Xuefeng Liu, Lei Yu, Ying Lin

Author Affiliations +

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126103T (2023) https://doi.org/10.1117/12.2671351
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Aiming at the problem that the coordinates of the existing fault point detection methods are inaccurate when determining the specific location of the fault point, this paper introduces the fault tree to design and study the over-current fault point detection method of the transmission cable ring network. For the normal and abnormal operating states of the transmission cable, determine the transmission cable's farthest over-current signal flip point fault string. The fault tree is introduced, and the over-current fault of the transmission cable ring network is substituted into the fault tree structure to realize the specific description of its characteristics; Finally, the particular location of the fault point is determined by rough measurement and precise measurement, and it is imported into the standard coordinates to realize the fault point detection. Compared with other detection methods, the positioning results obtained by the new detection method are more realistic, the detection accuracy is higher, and the specific location of the fault can be accurately found.

Citation Download Citation

Junpeng Dang, Jinhai Yang, Xuefeng Liu, Lei Yu, and Ying Lin "Research on detection method of over-current fault point of transmission cable ring network based on fault tree", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126103T (28 April 2023); https://doi.org/10.1117/12.2671351

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