Journal of Systems Engineering and Electronics ›› 2011, Vol. 33 ›› Issue (4): 958-962.doi: 10.3969/j.issn.1001-506X.2011.04.48

• 可靠性 • 上一篇    下一篇

基于改进PSO算法的实时故障监测诊断测试集优化

王宏力, 张忠泉, 崔祥祥, 宋涛   

  1. 第二炮兵工程学院, 陕西 西安 710025
  • 出版日期:2011-04-25 发布日期:2010-01-03

Test optimization of realtime monitoring and fault diagnosis system based on improved particle swarm optimization

WANG Hong-li, ZHANG Zhong-quan, CUI Xiang-xiang, SONG Tao   

  1. The Second Artillery Engineering Institute, Xi’an 710025, China
  • Online:2011-04-25 Published:2010-01-03

摘要:

针对基于相关性模型的复杂系统实时故障诊断问题,引入一种改进的多目标离散粒子群优化算法对测试集进行优化选择,以提高诊断系统效率,降低测试成本。基于现有粒子群优化算法,将粒子速度更新和位置更新的意义与测试选择相联系,提出了新的速度和位置更新公式;针对测试集故障检测数、故障隔离数、测试个数及成本等多个指标,分别设计了故障监测测试集和诊断测试集的多目标适应度函数,并给出最优解的多目标更新方法。仿真结果表明:改进算法收敛速度快,计算精度高,可为实时监测诊断系统测试集优化选择提供有效指导。

Abstract:

In order to obtain the optimal test set for a real time monitoring and fault diagnosis system based on dependency model with high efficiency and low cost, a modified particle swarm optimization (PSO) algorithm of multi objects is proposed. Taking the reasons why a test should be left in the optimal test set into consideration, two specified updating methods are introduced to find the set with optimal multi criteria, such as number of fault detected and isolated, number of test and cost, object functions, and the updating method for optimal particles is also modified specially. The simulation results show that the proposed algorithm has better computation efficiency and precision, which can give effective direction to the test selection of the realtime monitoring and fault diagnosis system.