高压电器2025，Vol.61Issue(6)：131-137,7.DOI:10.13296/j.1001-1609.hva.2025.06.015
基于混沌算法对电力变压器质量检测诊断和测试
Quality Detection,Diagnosis and Testing of Power Transformer Based on Chaotic Algorithm
摘要
Abstract
Transformer is an important component of power supply,and the testing method of dissolved gas in oil is usually used for quality inspection of distribution transformer so to diagnose its faults.In this paper,an improved op-timization algorithm is proposed and the dissolved gases analysis(DGA)is used for quality detection of power trans-former and thus for fault prediction.Firstly,the DGA data from of transformer is collected from various sources and the best mixed feature set is selected as the input to the model.For feature selection,the kernel principal component analysis(KPCA)is used.For optimizing the least squares support vector machine(LSSVM)model and constructing a quality detection diagnostic model,a hybrid optimization algorithm combining chaotic archimedes optimization algo-rithm(CAOA)and LSSVM is proposed,and the proposed CAOA and other models as well as the suggested model are compared.The test results show that the proposed CAOA is more accurate than other traditional methods in detecting the fault of transformer.关键词
优化算法/诊断/电力变压器/测试/检验Key words
algorithm optimization/diagnosis/power transformer/testing/inspection引用本文复制引用
田霖,张达,刘振,吴宏波,鄢晶..基于混沌算法对电力变压器质量检测诊断和测试[J].高压电器,2025,61(6):131-137,7.基金项目
国网河北省电力有限公司科技项目(KJ2021-018).Project Supported by State Grid Hebei Electric Power Co.,Ltd.Technology Project(KJ2021-018). （KJ2021-018）
