测试不可靠条件下基于精华蚂蚁系统的诊断策略优化方法

Optimization method of diagnosis strategy based on elite ant system under unreliable test conditions

诊断策略优化设计是测试性设计过程中重要一环,不可靠测试因素严重影响优化设计过程。在前人研究成果的基础上,针对启发式搜索算法难以解决不可靠测试条件下的诊断策略优化问题,提出了一种基于精华蚂蚁系统的诊断策略优化算法。首先建立了测试不可靠条件下诊断策略优化问题的数学模型;后以测试成本与错误代价为构建了优化目标;随后利用针对诊断策略优化问题改进过的精华蚂蚁系统算法对该问题进行求解;最后应用该算法针对某装备进行实例分析,通过与贪婪算法、普通蚁群算法的对比,体现出该算法的在精度与收敛速度方面的优势,验证了算法的可行性与有效性。

The optimization design of diagnosis strategy is an important part in the process of testability design. Unreliable test factors seriously affect the optimization design process. This paper summarizes previous research results. Aiming at the problem that heuristic search algorithm is difficult to solve the problem of diagnosis strategy optimization under unreliable testing conditions, this paper proposes a diagnosis strategy optimization algorithm based on the essence ant system. This paper establishes a mathematical model for the optimization of the diagnosis strategy under unreliable conditions, and then constructs the optimized target with the cost of testing and the cost of error. Then, it uses the improved ant system algorithm to solve the problem. Finally, the algorithm is applied to an equipment for instance analysis. Compared with greedy algorithm and common ant colony algorithm, it shows the advantages of the algorithm in precision and convergence speed, and verifies the feasibility and effectiveness of the algorithm.