Optimal Test Point Placement Based on Fault Diagnosability Quantitative Evaluation

Abstract

The optimal test point placement problem in existing research results is mainly limited to the qualitative study of whether faults can be diagnosed without considering the difficulty of diagnosing faults. We proposed an optimal test point placement approach based on fault diagnosability quantitative evaluation to solve the above problem. First, the fault diagnosability is quantitatively evaluated based on the maximum mean discrepancy (MMD). Then, the problem of optimal test point placement is considered a multi objective optimization problem. The optimal test point set is solved using the multi objective sparrow search algorithm (MOSSA) based on the fault diagnosability quantitative evaluation results, considering limitations on the test point number, reliability, and cost. Finally, the proposed approach is used to optimize the placement of test points in the switching power supply system. The simulation results show that only three test points need to be placed to make the system meet the fault diagnosability requirements. Two test point placement schemes are obtained, which can be selected according to different practical requirements. The experimental results illustrate that the proposed approach can optimize the system test point placement while ensuring good fault diagnosability.

Keywords

• Fault diagnosability
• quantitative evaluation
• maximum mean discrepancy
• test point placement
• sparrow search algorithm