Bayesian virtual sensing for full-field dynamic response estimation

Structural monitoring and control utilize vibration measurements acquired by a sensor network. Combined empirical and analytical virtual sensing is introduced to estimate full-field dynamic response of a structure using a limited number of sensors. First, empirical virtual sensing techniques are applied to obtain less noisy estimates of sensor data. Then, analytical virtual sensing utilizes the finite element model and the empirical estimates to compute the full-field response. The effect of the noise estimation error on the accuracy of virtual sensors is studied and the upper bound of the noise variance is derived. Numerical simulations are performed for a structure subject to unknown random excitation in order to validate and compare different virtual sensing algorithms. (C) 2017 The Authors. Published by Elsevier Ltd.