Diagnosis for Vibration Fault of Steam Turbine Based on Modified Particle Swarm Optimization Support Vector Machine

摘要：

Due to the influence of artificial factor and slow convergence of particle swarm algorithm (PSO) during parameters selection of support vector machine (SVM), this paper proposes a modified particle swarm optimization support vector machine (MPSO-SVM). A Steam turbine vibration fault diagnosis model was established and the failure data was used in fault diagnosis. The results of application show the model can get automatic optimization about the related parameters of support vector machine and achieve the ideal optimal solution globally. MPSO-SVM strategy is feasible and effective compared with traditional particle swarm optimization support vector machine (PSO-SVM) and genetic algorithm support vector machine (GA-SVM).

关键词： support vector machine vibration diagnosis particle swarm optimization genetic algorithm

作者: Shi zhi-biao Song quangang Ma mingzhao

作者单位: School of Mechanical Engineering,Northeast Dianli University,Jilin 132012

会议类型: 国际会议

会议名称: 4th International Conference on Measuring Technology and Mechatronics Automation(第四届检测技术与机电自动化国际会议 ICMTMA 2012)

会议地点: 三亚

会议语种:英文

页码: 113-116

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）