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首页>《中国测试》期刊>本期导读>基于改进蚁群的测试序列优化算法

基于改进蚁群的测试序列优化算法

1610    2016-01-16

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作者:李丹阳, 蔡金燕, 杜敏杰, 朱赛

作者单位:军械工程学院光学与电子工程系, 河北 石家庄 050003


关键词:测试序列优化; 蚁群算法; 二值属性系统; 动态树


摘要:

针对故障诊断中的测试序列优化问题,提出一种改进蚁群算法的解决方法。该方法根据二值属性系统的特点,定义状态集向量及测试向量,将故障测试隔离过程转化为向量的位运算过程,将序列优化问题转化为一种最小代价的动态树构造问题,设计灵活的状态转移规则,并根据动态树的分层结构特点,提出一种分层加权和遗传变异相结合的信息素更新策略,解决这种动态树结构的寻优问题。仿真结果表明:该算法以较高的效率收敛到已知最优解,高效实用,为大规模复杂系统的测试优化问题提供了一条新的解决途径,具有一定的工程应用价值。


Test sequencing optimization based on improved Ant Algorithm

LI Dan-yang, CAI Jin-yan, DU Min-Jie, Zhu Sai

Department of Electronic and Optical Engineering, Ordnance Engineering College, Shijiazhuang 050003, China

Abstract: For solving the problem of test sequencing optimization in fault diagnosis, an improved ant algorithm was presented in this paper.According to the feature of the binary attribute system, state-set vector and test-set vector were defined, the fault testing segregation process was transformed to the process of vector operation and the problem of test sequencing optimization was transformed to construct a dynamic tree with minimum cost.Transfer rule of the ant state was designed and a kind of layered weighted pheromone update mechanism was presented, which combine with the variation in GA and solved the optimization problem of tree-construction.Simulation results show that the algorithm convergences to the optimal solution with high efficiency and provides a new way to solve the test sequencing optimization for large-scale complicated system.

Keywords: test sequencing optimization; ant algorithm; binary attribute system; dynamic tree

2013, 39(4): 105-108,128  收稿日期: 2012-5-2;收到修改稿日期: 2012-7-11

基金项目: 河北省重点基础研究项目(10963529D)

作者简介: 李丹阳(1987-),男,河南濮阳市人,硕士研究生,专业方向为电子系统性能检测与故障诊断。

参考文献

[1] Pattipati K R, Alexandridis M G. Application of heuristic search and information theory to sequential fault diagnosis[J]. IEEE Trans on Systems,Man and Cybernetics,1990,20(4):872-887.
[2] Fang T, Pattipati K R. Rollout strategies for sequential fault diagnosis[J]. IEEE Trans on Systems,Man and Cybernetics,2003,33(1):86-99.
[3] 黄以锋,景博. 基于Rollout算法的多值属性系统诊断策略[J]. 控制与决策,2011,26(8):1269-1272.
[4] 石君友,田仲. 故障诊断策略的优化方法[J]. 航空学报,2003,24(3):212-215.
[5] 杨成林,田书林,龙兵. 多值故障字典的测点选择与序测试设计[J]. 系统工程与电子技术,2009,31(9):2271-2275.
[6] 李赟,蔡志明. 大型复杂系统测试序列优化[J]. 计算机集成制造系统,2010,16(9):1961-1966.
[7] 李士勇,陈永强,李研. 蚁群算法及其应用[M]. 哈尔滨:哈尔滨工业大学出版社,2004(9).
[8] 郭禾,程童,陈鑫,等. 一种使用视觉反馈与行为记忆的蚁群优化算法[J]. 软件学报,2011,22(9):1994-2005.
[9] 蒋荣华,王厚军,龙兵. 基于DPSO的改进AO*算法在大型复杂电子系统最优序贯测试中的应用[J]. 计算机学报,2008,31(10):1835-1840.