基于自适应Kalman滤波GNSS‑RTK与加速度数据融合的桥梁结构位移重构方法

Bridge Structural Displacement Reconstruction Method Based on Fusion of Adaptive Kalman‑Filtered GNSS‑RTK Data and Acceleration Data

主梁位移是大跨度桥梁安全评估和损伤诊断的重要指标,也是桥梁健康监测系统中的重点监测目标,为提高基于全球卫星导航系统的动态精度定位(Global Navigation Satellite System-Real Time Kinematic,GNSSRTK)位移数据的准确性和可靠性,提出了基于自适应Kalman滤波GNSS-RTK数据与加速度数据融合的桥梁结构位移重构方法,实现了低频GNSS位移数据与高频加速度数据融合,进一步提高了实时位移数据的测量精度与频率,解决了GNSS-RTK数据缺乏高频位移分量的问题。最后以泰东黄河大桥为例,结合有限元方法验证了该位移重构方法在大跨度桥梁位移重构过程中的可靠性和有效性,为提高桥梁结构实时位移监测的精确度提供了一定的理论支撑与参考。

The displacement of the main beam is an important indicator for safety assessment and damage diagnosis of long-span bridges,as well as a key monitoring target in bridge health monitoring systems.To improve the accuracy and reliability of GNSS-RTK displacement data,this paper proposes a bridge structural displacement reconstruction method based on the fusion of adaptive Kalman-filtered GNSS-RTK data and acceleration data.This method achieves the fusion of low-frequency displacement data with high-frequency acceleration data,the measurement precision and frequency of real-time displacement data are further enhanced,addressing the lack of high-frequency displacement components in GNSS-RTK data.Finally,taking the Taidong Yellow River Bridge as an example,the reliability and effectiveness of this displacement reconstruction method in the displacement reconstruction process of long-span bridges are verified using the finite element method.The research results provide theoretical support and reference for improving the accuracy of real-time displacement monitoring of bridge structures.