Test point optimization selection based on quantitative fault propagation analysis

Abstract

Test point optimization selection is an effective way to decrease test cost and time. This paper proposes a method of test point optimization selection based on qualitative fault propagation analysis. Firstly, a qualitative fault propagation model based on physical relations is built. Secondly, the responses of available test points under normal state and failure state are analyzed, and the Mahalanobis distances from the normal state to the failure state in each test point are calculated. Thirdly, the corresponding test point of the largest Mahalanobis distance is selected to monitor and track fault growth. An amplitude-modulation circuit is used to verify the feasibility and effectiveness of the proposed method. The results show that the proposed technology is important to select and optimize the test point in order to improve their testability performance level.