Sensor placement design for SHM under uncertainty

Structural Health Monitoring (SHM) systems increase aerospace vehicle safety and reliability, while reducing vehicle operating and maintenance costs. Many advances have been made in terms of sensors, materials, damage detection algorithms, structural reliability, finite element analysis, and deterministic sensor placement optimization (SPO) algorithms. Additional research needs to be focused on probabilistic modeling, analysis, and design, as well as SPO under uncertainty. This paper discusses a methodology to integrate the advances in various disciplines for the optimum design of SHM systems under uncertainty. This includes finite element analysis under varying loads and incorporation of uncertainty quantification methods. Validating the finite element model with experimental data and accounting for uncertainties of experimental measurements and model predictions are also part of this analysis. The SHM sensors need to be placed optimally in order to:detect with high probability and reliability any structural damage before it turns critical. The proposed methodology achieves this objective by combining stochastic finite element analysis, structural damage detection analysis, and SPO.