Towards real-time health monitoring of structural systems via recursive Bayesian filtering and reduced order modelling

A method for the structural health monitoring (SHM) of compliant, thin plates is discussed. With a specific focus on lightweight composite structures, a proposal for the optimal deployment of a network of surface-mounted inertial micro-sensors (MEMS) is reviewed. Allowing for the measurements gathered through the sensor network as (partial) observations of the structural state, a hybrid Kalman-particle filtering scheme is adopted to track the response of the plate to the external excitations and simultaneously identify unknown model parameters, among which damage or integrity indices. To move towards a real-time SHM procedure, the mentioned tracking and identification tasks are performed on a reduced-order model of the structure, continuously tuned after damage inception by a further Kalman filter. Results are reported for the exemplary case of a square plate, simply supported along its boundary, loaded by a concentrated force at its centre and developing a uniform damage in regions of its mid-plane area.