Optimal sensors positioning for condition-based risk assessment by particle swarm optimization

Value of Information (VoI) has been proposed for optimal sensors positioning on Systems, Structure, and Components (SSCs). The non-sub-modularity property of VoI calls for non-greedy optimization methods for the solution of the positioning optimization problem. In this work, we use Particle Swarm Optimization (PSO) for solving the optimal sensors positioning problem and condition-based risk assessment. A practical case study is considered regarding the positioning of sensors measuring the thickness of a manifold of a Steam Generator (SG) for a Prototype Fast Breeder Reactor (PFBR) that can fail due to creep. Results show that the PSO-optimized sensors positions provide results that enable more accurate risk estimates than using greedy optimization methods.