Extended fault-pair Boolean table based test points selection for robotic systems

Abstract

Analog circuit fault isolation is crucial for ensuring the reliability and performance of robotic systems. Test point selection plays a key role in enabling effective fault isolation, yet traditional methods often struggle to balance the number of test points with fault isolation accuracy. This paper proposes a novel test point selection method by extending the fault-pair Boolean table into a distributional framework. The approach enhances test point selection by employing the Bhattacharyya Coefficient to quantify distributional overlap and using kernel density estimation (KDE) to model circuit response distributions without assuming normality. To further improve estimation accuracy, the Grey Wolf optimization algorithm is applied for optimal KDE bandwidth selection. Experimental results on a negative feedback circuit show that the proposed method successfully isolates all 11 faults, demonstrating strong isolation capability. Further validation on an active filter circuit confirms its effectiveness, achieving successful isolation of 16 out of 20 faults. Compared to other methods, the proposed approach consistently yields higher fault isolation across various thresholds.

Keywords

Robotic systems / analog circuit / fault isolation / fault-pair Boolean table / kernel density estimation / Bhattacharyya coefficient / grey wolf optimization