Title:

An Output-only Bayesian State Estimator for Partially Observed Structural Systems

This study contributes to the state-of-the-art in structural system identification and facilitates virtual sensing and digital twinning of civil infrastructure systems in operational conditions. A key challenge in the development of digital twinning and system identification of operational civil infrastructure is the variability of system input, e.g. operational loads. Herein a novel algorithm is presented for an unbiased output-only state estimation for linear state space systems with direct feedthrough. In this paper the problem of state estimation for discrete time systems, where no previous assumption is made regarding the input, is addressed. A two-stage output-only filter is proposed, and its unbiasedness is proven, and the error covariance propagation over time is derived. The first case study corresponds to a shear building subjected to a random ground acceleration. The second case study shows the results for simulated experiments over a finite element model of a steel railway bridge. The results of the simulated experiments show a good agreement between the “true response” and the filter state estimation. It is shown that the developed method outperforms state-of-the-art output-only methods for state and input estimation.

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