Abstract:

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.