电力系统保护与控制Issue(17)：103-107,5.
基于差分进化算法的模糊核聚类算法及其在故障诊断中的应用
Fuzzy kernel-clustering algorithm based on differential evolution algorithm and its application in fault diagnosis
摘要
Abstract
In allusion to the determination of the kernel parameters and the effective evaluation of the clustering results of Fuzzy Kernel-clustering Algorithm (FKCA), differential evolution algorithm (EA) is used to search the optimal kernel parameter and the clustering centers. Furthermore, the Xie-Beni index is promoted to the kernel space, and a new fitness function is designed to improve the clustering performance. The proposed method is applied in the standard benchmark as well as the motor bearing fault dataset. The results shows that the proposed method is a promising clustering method for fault diagnosis.关键词
模糊聚类/核函数/差分进化算法/故障诊断Key words
fuzzy clustering/kernel function/differential evolution algorithm/fault diagnosis分类
信息技术与安全科学引用本文复制引用
张新萍,张孝远,刘杰..基于差分进化算法的模糊核聚类算法及其在故障诊断中的应用[J].电力系统保护与控制,2014,(17):103-107,5.基金项目
河南工业大学高层次人才基金项目（2013BS059） This work is supported by High-level Personnel Funds of Henan University of Technology (No.2013BS059) （No.2013BS059）
