基于粒子群算法的电力变压器绕组故障诊断方法  

Power Transformer Winding Fault Diagnosis Method Based on Particle Swarm Optimization

作　　者：陈东亮 张龙[1] CHEN Dongliang;ZHANG Long(Anhui Electric Power Engineering Supervision Co.,Ltd.,Hefei 230071,China)

机构地区：[1]安徽电力工程监理有限公司,安徽合肥230071

出　　处：《通信电源技术》2022年第5期36-38,共3页Telecom Power Technology

摘　　要：由于传统的电力变压器绕组故障诊断方法在精度上有一定的误差,因此提出一种基于粒子群算法(Particle Swarm Optimization,PSO)的电力变压器绕组故障诊断方法。构建粒子群网络,对变压器绕组数据进行处理;初始化粒子群寻找适配粒子,完成粒子分类;构建分离模型进一步识别引起变压器绕组故障的信号数据,实现电力变压器绕组故障诊断。通过实验证明了所提方法在变压器绕组故障诊断中的诊断精度较高,具有较好的实际应用性能。Because the traditional power transformer winding fault diagnosis method has certain errors in accuracy,a power transformer winding fault diagnosis method based on Particle Swarm Optimization(PSO)is proposed.Build a particle swarm network to process the transformer winding data;initialize the particle swarm to search for suitable particles to complete particle classification;build a separation model to further identify the signal data that causes transformer winding faults,and realize power transformer winding fault diagnosis.Experiments show that the proposed method has high diagnostic accuracy in transformer winding fault diagnosis and has good practical application performance.

关 键 词：粒子群算法(PSO) 电力变压器 绕组故障诊断 

分 类 号：TM4[电气工程—电器]