Fault diagnosis of rotating machinery based on fuzzy clusteringoptimized by chaos embedded particle swarm optimization
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    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.

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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

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  • Received:January 20,2011
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