Structural health monitoring by Bayesian updating

The problems of structural damage detection and reliability assessment are closely related, and should be dealt with in a unified approach. In fact, the health monitoring of a damaged construction requires both damage detection and the assessment of the effects of damages on the life-cycle reliability. In this paper, a complete procedure for structural health monitoring is briefly illustrated and applied. The problem of damage detection is dealt with by an identification technique with unknown input; a Bayesian model updating procedure, based on an adaptive Markov Chain Monte Carlo method, is adopted to quantify, in probabilistic terms, the structural damage based on data from monitoring. An advanced simulation technique, Subset Simulation, is then used to assess the probability of exceeding any structural response level taking into account the various sources of uncertainty. It is observed that the Bayesian approach is really efficient in characterizing the structural damage and its effects.