Journal of Systems Engineering and Electronics ›› 2013, Vol. 35 ›› Issue (3): 672-676.doi: 10.3969/j.issn.1001-506X.2013.03.39

• 可靠性 • 上一篇    

基于进化理论的故障模式判别算法

王久崇1,2, 樊晓光1, 褚文奎1, 丛伟1, 李建勋1   

  1. 1. 空军工程大学航空航天工程学院, 陕西 西安 710038;
    2. 中国人民解放军93868部队, 宁夏 银川 750025
  • 出版日期:2013-03-20 发布日期:2010-01-03

Fault mode identification method based on evolutionary theory

WANG Jiu-chong 1,2, FAN Xiao-guang1, CHU Wen-kui1, CONG Wei1, LI Jian-xun1   

  1. 1. College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi’an 710038, China;
    2. Unit 93868 of the PLA, Yinchuan 750025, China
  • Online:2013-03-20 Published:2010-01-03

摘要:

基于特征参数的故障模式判别是一个组合优化问题。在评析已有进化方法的基础上,建立了航空电子系统的故障模式判别模型,提出了一种将正交遗传算子(orthogonal genetic arithmetic operators, OGAO)融入到粒子群算法(particle swarm optimization, PSO)中的组合寻优方法,并进行了一定的改进。该方法能有效避免局部极小,较好地处理离散变量的组合优化问题,有利于提高解的精度和收敛速度。以某型机载综合数据采集器的电源模块为平台进行实验仿真,结果证明了本文算法的正确性和优越性。

Abstract:

Fault mode identification based on characteristic parameter is a problem of combinatorial optimization. Based on an analysis of the evolutionary method, the fault mode identification model of the avionics system is founded, and an improved combinatorial optimization method fusing particle swarm optimization (PSO) and the orthogonal genetic arithmetic operator (OGAO) is proposed. The advantages of this method can be drawn, the local optimum can be avoided, the combinatorial optimization problem of the discrete variable can be disposed better, which is advantageous to the improvement of the speed of convergence and solution accuracy. The experiment result on a power module using in the airborne integrated data acquisition device shows. the correctness and superiority of the proposed method.