Probabilistic design of smart sensing functions for failure diagnostics and prognostics

This paper presents a robust design framework to develop piezoelectric materials based structural sensing systems for failure diagnostics and prognostics. At first, a detectability measure is proposed to evaluate the performance of any given sensing system given varioaus uncertainties. Thus, the censoring system design problem can be formulated to maximize the detectability of the censoring system through optimally allocating piezoelectric materials into a target structural system. Secondly, the formulated problem can be conveniently solved using reliability-based robust design framework to ensure design robustness while considering the uncertainties. A rectangular plate is employed to demonstrate the effectiveness of the design framework in developing multifunctional material sensing systems.