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Yi Li

at Xi'an Jiaotong Univ.

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Proceedings Article | 11 November 2022 Paper

Fault simulation and identification of capacitive casings based on fault tree theory

He Liu, Daiyong Yang, Lixin Jiao, Junbo Liu, Shouxue Li, Yi Li

Proceedings Volume 12301, 123012P (2022) https://doi.org/10.1117/12.2644657

KEYWORDS: Capacitance, Metals, Particles, Dielectrics, Sensors, Transformers, Data modeling, Failure analysis, Capacitors, Manufacturing

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The safe and stable operation of the power system is related to the quality and efficiency of national production. With the mature development of the detection technology of large power equipment, online monitoring has gradually become an important means of detecting the insulation status of equipment. Casings, as the core component of power transformer, bears the electromagnetic environment of high voltage and strong electric field in operation, and has multiple interfaces (oil-air interface). The complex working environment of casing leads to the occurrence of faults, so it has high engineering value to study the on-line monitoring system of Casing. Firstly, this article designed casing shrinkage ratio model, and make tail damp and metal particle discharge fault artificially. Secondly, we extract five kinds of characteristic value in the laboratory including the capacitance variation, the dielectric loss tangent, the maximum discharge amplitude, the maximum amplitude and the average discharge pulse number. At last, we used the analytic hierarchy process (AHP) to build the fault tree model for fault diagnosis and classification of two kinds of discharge.

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