Optimal Sensor Placement Based on System Reliability Criterion Under Epistemic Uncertainty

Abstract

Fault diagnosis usually requires lots of data that are collected through sensors mounted on some locations in the system. Performance of a diagnostic system is largely dependent upon the number and locations of sensors. Accordingly, optimization of sensor placement has a significant influence on the efficiency of fault diagnosis. In this paper, a novel sensor placement based on a system reliability criterion is proposed, which aims to deal with the failure dependence and epistemic uncertainty. Specifically, it develops a dynamic fault tree (DFT) model to describe the dynamic failure behaviors based on failure mode and effects analysis and uses the interval numbers to express the failure rates of components. Furthermore, an indicator of sensor placement, named diagnostic importance factor (DIF), is calculated by mapping a DFT into a dynamic evidential network, and a sorting method based on the relative superiority degree is used to determine the potential locations according to DIF of components. In addition, the failure probability of the top event is considered as the criterion for sensor placement optimization and all scenarios of sensor placement are prioritized based on the criterion. Finally, the effectiveness of the proposed method is demonstrated via application to a real braking system.