重庆大学学报2011，Vol.34Issue(6)：26-30,5.
混沌粒子群优化模糊聚类的旋转机械故障诊断
Fault diagnosis of rotating machinery based on fuzzy clustering optimized by chaos embedded particle swarm optimization
摘要
Abstract
A method of weighted fuzzy clustering optimized by chaos embedded particle swarm algorithm (CPSO) is put forward and applied in vibration fault diagnosis of rotating machinery. In the method, CPSO is used to displace the traditional stochastic-gradient algorithm to optimize parameters of weighted fuzzy C-means (WFCM). The best clustering num and clustering centers are automatically attained according to clustering validity function. The experimental results show that the method effectively increases the convergence velocity and precision of WFCM and so does the correctness rate of fault diagnosis for rotating machinery.关键词
旋转机械；故障诊断；混沌；粒子群优化；模糊C-均值Key words
rotating machinery/ fault diagnosis/ chaos/ particle swarm optimization/ fuzzy C-means分类
能源科技引用本文复制引用
胡方霞,谢志江,岳茂雄..混沌粒子群优化模糊聚类的旋转机械故障诊断 [J].重庆大学学报,2011,34(6):26-30,5.基金项目
国家自然科学基金资助项目(10976034) （10976034）
