计算机科学
变压器
电流互感器
电气工程
工程类
电压
作者
Junyi Cai,Lijun Zhou,Junjie Hu,Chenqingyu Zhang,Wei Liao,Lanping Guo
标识
DOI:10.1049/iet-smt.2019.0051
摘要
This study proposes a high-accuracy method of localising partial discharge (PD) for transformer fault diagnosis. This study aims to solve the problem of high-accuracy estimation of PD in transformers by detecting the acoustic signals. First, by combining the advantages of the differential evolution (DE) algorithm and the particle swarm optimisation (PSO) algorithm, the authors describe a hybrid DE-PSO algorithm that can maintain great diversity even at the later stage of calculation. For further accuracy, a cooperative localisation differential evolution-particle swarm optimization-correction-Newton's method (DPCN) algorithm based on the DE-PSO algorithm and Newton's method with consideration of corrected time difference of arrival values is proposed. The results of simulations and experiments show that the proposed algorithm has excellent performance with high accuracy and strong robustness, and it can meet the needs of field applications.
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