基于Kalman滤波下的高铁隧道沉降变形评估方法

摘要

在进行高铁隧道沉降变形评估时，由于隧道的沉降量小，受随机噪声干扰较大，使得原始监测数据的沉降曲线波动较大，出现尖端点现象。本文运用 Kalman 滤波对原始监测数据进行去噪，根据经过去噪后的原始监测数据进行隧道沉降变形评估。工程实例对比分析表明，经过Kalman滤波去噪之后，可有效地消减原始监测数据中的随机噪声，使沉降曲线更平滑且更逼近真实沉降情况；基于Kalman滤波下的沉降变形评估的相关系数及可靠性较传统的评估方法有所提高，该评估方法在高铁隧道沉降变形评估中体现出更好的优越性及较好的应用效果。%In assessing high-speed railway tunnel settlement deformation , small tunnel settlement and noise in-terference, the monitoring data will increase and tip point phenomenon emerges.Kalman filter is used to de-noise the original data and assess the tunnel deformation according to the donoised original monitoring data . Comparing and analyzing the engineering examples can efficiently eliminate the random errors in original data and make the settlement curve more smooth and approach the real settlement by Kalman filter .Correlation coef-ficient and reliability of the settlement deformation assessment based on Kalman filtering are improved than tradi-tional assessment methods.Superiority and application are realized in high-speed railway tunnel settlement de-formation assessment .