Dynamic Response Reconstruction to Supplement the Data Insufficiency
Due to sensor cost and installment accessibility, it is not practical to instrument sensors on every point of a structure and the measured set of dynamic responses is thus usually incomplete, thus the need to perform dynamic response reconstruction always arises, especially for a large civil structure. This study presents the novel Kalman filter (KF) based response reconstruction methods under known and unknown excitations. The underlying state estimation theories under known and unknown excitation are first introduced. Then dynamic response reconstruction methods are developed based on the state estimation in the framework of KF. For easy explanation and demonstration, a simple 4-story shear-type frame is employed in numerical study. The performances of the proposed KF based response reconstruction are examined. The effect of process and measurement noises covariance and spatial location of the measurement sensors to the reconstruction accuracy is investigated and discussed.
KeywordsDynamic response reconstruction Kalman filter Joint response Excitation reconstruction
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