A dynamic Bayesian network framework for risk assessment of systems based on sensor measurements Tien, Iris; Pozzi, Matteo; Der Kiureghian, Armen
In this paper, a framework based the dynamic Bayesian network (DBN) is proposed to dynamically monitor the response of structures to hazards. The methodology enables the probabilistic analysis of the response of a system to a hazard that is stochastic, e.g., an earthquake ground motion, as it dynamically evolves in time, based on sensor measurements that are uncertain. The developed DBN framework is applied to the estimation of the inter-story drift of a multi-story shear-type building under earthquake hazard based on accelerometer measurements. Using a simulation approach, the ability of the method to accurately assess the system response is shown. In addition, robustness of the method to system uncertainties, including uncertainties in the structural characteristics, is demonstrated.
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