Structural Response Estimation Based on Kalman Filtering with Known Frequency Component of External Excitation and Multitype Measurements for Beam-Type Structure

Structural health monitoring can be performed through long-term monitoring of key structural parts to obtain the structural response information of civil engineering structures in real service environments. This enables the provision of on-site measurement data for in-depth understanding of the structural performance and verifying design parameters. To address the issue of limited information from sensors, this paper proposes a structural response estimation method based on Kalman filtering and multitype measurements for beam-type structures. Starting from the structural motion equation, an internal structural model equation by extracting the modal external excitation frequency component and the structure's inherent characteristics are used for structural response estimation. The frequency component of external excitation should be known in the proposed method. Then, based on the multitype measurements, the system and observation noises are considered, and a structural response estimation equation based on Kalman filtering is formulated. Finally, particle swarm optimization is applied to optimize the Kalman error parameter values and achieve multilocation and multitype structural response estimation based on the multitype measurements. The effectiveness and feasibility of the proposed method are verified via experimental analysis of the Binzhou Yellow River Bridge mode, where only pedestrian loading is used.