Online displacement extraction and vibration detection based on interactive multiple model algorithm

Abstract Vibration detection and displacement extraction of structures are of great significance to structural health monitoring(SHM). Accelerometers are one of the most widely used sensors in SHM, but displacement is not the direct output of accelerometers. There has been substantial research undertaken on the state parameter estimation of structure. Most studies in the field of structural state estimation have only focused on offline structure analysis. Few empirical studies have focused on online displacement extraction and verification. The present study aimed to explore an adaptive online displacement extraction and vibration detection method with only acceleration measurement. The methodological approach taken in this study is a mixed methodology based on the interactive multiple model (IMM) Kalman filter. Vision-based displacement extraction and segmental integration based displacement extraction are designed as verification schemes. Four groups of experiments were carried out to verify the proposed method. The findings show that the damping vibration model is suitable for capturing obvious vibration, the constant acceleration model is suitable for capturing slight vibration, and the constant position model is suitable for static state tracking. For obvious vibration, the IMM Kalman filter can be effectively performed for displacement extraction and vibration detection. For slight vibration, the performance of the IMM segmental integration is good. It is hoped that this research will contribute to a deeper understanding of displacement extraction and vibration detection in SHM.