基于模拟退火算法的实时故障诊断测试集优化

为解决复杂系统的实时故障诊断问题，设计基于模拟退火（simulatedannealingalgorithm，SAA）的测试集多目标优化策略。从测试集故障隔离率、测试个数及成本等多个指标优化入手，对每个优化目标按其重要性进行降序排列，依据优先顺序依次实现多个目标的优化，并引用阿波罗号发射前系统状态检测的例子进行验证。仿真结果表明：模拟退火算法原理简单，计算精度高，可为实时系统诊断测试集优化选择提供有效指导。

Test Set Optimization of Real-Time Fault Diagnosis System Based on Simulated Annealing Algorithm

In order to solve the real-time fault diagnosis problem of complex system,a multi-objective optimization strategy of test set based on simulated annealing algorithm(SAA) is designed.Starting with optimal multi-criteria such as fault isolation rate,number of tests and cost,each objective is sorted in descending order consistent with its importance and realized in accordance with its priority.The example of Apollo system state detection before launch is introduced to validate its ability.The simulation results show that the SAA principle is simply and better precision,which can give effective direction to the test selection of real-time fault diagnosis system.