CAJ | 학술논문

随着电网规模的日益庞大，对高压断路器的安全运行提出了越来越高的要求。本文就核主元分析（KPCA）方法应用于高压断路器的故障诊断进行了研究。该方法针对高压断路器故障数据多维非线性的特点，通过计算其合闸电流信号原始数据空间的内积核函数来实现原始数据到特征空间的非线性映射，然后在特征空间内构2造T和SPE统计量检测过程中发生的故障，并对故障进行分类。本文以VMB5-12型10kV真空断路器弹簧操动机构为试验样机采集数据，仿真实验结果表明，该方法具有较高的稳定性，能够有效地对故障数据进行特征提取。
수착전망규모적일익방대，대고압단로기적안전운행제출료월래월고적요구。본문취핵주원분석（KPCA）방법응용우고압단로기적고장진단진행료연구。해방법침대고압단로기고장수거다유비선성적특점，통과계산기합갑전류신호원시수거공간적내적핵함수래실현원시수거도특정공간적비선성영사，연후재특정공간내구2조T화SPE통계량검측과정중발생적고장，병대고장진행분류。본문이VMB5-12형10kV진공단로기탄황조동궤구위시험양궤채집수거，방진실험결과표명，해방법구유교고적은정성，능구유효지대고장수거진행특정제취。
The gradually expansion of power grids makes the safe operation of HVCBs face high demands increasingly. Therefore, this paper proposes Kernel Principal Component Analysis (KPCA) method in order to diagnose the faults of HVCBs. As the fault data of HVCBs has the characteristics of multi-dimensional nonlinearity, this method calculates inner kernel function of HVCBs′closing current in the original data space so as to achieve nonlinear mapping of the original data to the feature space. Then faults can be detected and classified in the feature space by establishing T 2 and SPE statistics. In this paper, as an experimental prototype, VMB5-12 10kV vacuum circuit breaker spring actuator is utilized to collect sample data. Simulation results show that the proposed approach can steadily and effectively extract characteristics of fault data.