中国机械工程2016，Vol.27Issue(15)：2055-2059,5.DOI:10.3969/j.issn.1004-132X.2016.15.012
一种聚类优化融合故障诊断方法及其应用
Clustering Optimization Fusion Method for Fault Diagnosis and Its Applications
摘要
Abstract
Single community diagnosis clustering methods were difficult to identify different fault states,in order to improve diagnostic accuracy,a fusion clustering method was proposed herein based on genetic optimization algorithm.Three clustering methods,the community clustering,the K-means clustering and the particle swarm clustering,were used to identify the fault states respectively.The diagnostic accuracies were used to construct an initial weight matrix.The genetic optimization algo-rithm was used to optimize the weight matrix.The examples of bearing fault diagnosis show that the clustering optimization fusion method may improve diagnostic accuracy.关键词
聚类分析/权值矩阵/融合诊断/遗传算法Key words
clustering analysis/weight matrix/fusion diagnosis/genetic algorithm分类
信息技术与安全科学引用本文复制引用
蒋玲莉,莫志军,陈安华,李学军..一种聚类优化融合故障诊断方法及其应用[J].中国机械工程,2016,27(15):2055-2059,5.基金项目
国家自然科学基金资助项目(51575177) （51575177）
湖南省教育厅优秀青年项目(14B057) （14B057）
湖南省教育厅资助重点项目(13A023) （13A023）
