基于测试重要度的Petri网序列优化算法

针对故障诊断测试序列优化问题，提出一种基于测试重要度的Petri网序列优化算法。该方法依据测试代价原则，并引入测试重要度函数，采用Petri网全局搜索算法，在传统测试优化目标测试费用和故障检测率的基础上，选择包含故障信息量大的测试，有效缩减测试序列的长度，并结合测试代价的反馈计算，减少总体测试费用。研究表明，所提出的优化算法克服了传统算法陷入局部优化的缺点，能够有效地减少总体测试代价。

Petri net sequence optimization algorithm based on test importance

A Petri net sequence optimization algorithm based on test importance is proposed for the test sequence optimization of fault diagnosis. Petri nets are used to search the global optimal test sequence according to the principle of the test cost. Furthermore, the test importance function is introduced into the optimization algorithm. Compared with the traditional optimization goals of test cost and fault detection rate, the informative test sequence which is adopted in this algorithm can effectively reduce the length of test sequences, and the feedback calculation can bring down the overall cost of test. Experiments show this proposed optimization algorithm can overcome the traditional algorithm shortcomings of local optimization and effectively reduce the test cost.