李 俊,冯俊杰,武文吉,刘迎澍.基于改进萤火虫算法和多分类支持向量机的变压器故障诊断[J].电测与仪表,2022,59(3):131-135. Li Jun,Feng Junjie,Wu Wenji,Liu Yingshu.Power transformer fault diagnosis based on improved firefly algorithm and multi-classification support vector machine[J].Electrical Measurement & Instrumentation,2022,59(3):131-135.
基于改进萤火虫算法和多分类支持向量机的变压器故障诊断
Power transformer fault diagnosis based on improved firefly algorithm and multi-classification support vector machine
Firefly algorithm, whose convergence speed and precision is improved by chaotic optimization theory and adaptive variable step size mechanism, is introduced to achieve fault diagnosis of power transformer efficiently. A power transformer fault diagnosis method based on improved firefly algorithm (IFA) and multi-classification support vector machine (SVM) is proposed. The method uses IFA to optimize the parameters of SVM. Multi-class SVM is constructed based on binary tree method to identify power transformer fault types in the method. The simulation results of power transformer fault diagnosis examples show that the convergence and optimization ability of IFA are better than those of FA and particle swarm optimization (PSO), and the optimized power transformer fault diagnosis model has higher accuracy.
