The Analysis of Parameters Selection of PSO Algorithm for Fault Diagnosis

摘要：

The particle swarm optimization (PSO) is an optimization algorithm based on intelligent optimization. Parameters selection of PSO is the key influence on performance and efficiency of the algorithm. In this paper, the performance of PSO is analyzed, based on the control parameters variants including particle number, accelerate constant, inertia weight and maximum limited velocity. And then these dynamic parameters of PSO have been applied on the neural network training for gearbox fault diagnosis, the results with different parameters of PSO are compared and analyzed. At last some suggestions for parameters selection are proposed.

作者: Xiuye Wei Hongxia Pan

作者单位: School of Mechanical Engineering and Automatization North University of China Taiyuan, Shanxi 030051

会议类型: 国际会议

会议名称: Fourth International Conference on Impulsive and Hybrid Dynamical Systems(ICIHDS 2007)(第四届国际脉冲和混合动力系统学术会议)

会议地点: 南宁

会议语种:英文

在线出版日期: 2007-07-20（万方平台首次上网日期，不代表论文的发表时间）