Wang Yan, Yang Dong-Hui, Yi Ting-Hua
School of Civil Engineering, Dalian University of Technology, Dalian 116023, China.
Sensors (Basel). 2021 Mar 11;21(6):1967. doi: 10.3390/s21061967.
Wind action is one of the environmental actions that has significant static and dynamic effects on long-span bridges. The lateral wind speed is the main factor affecting the lateral displacement of the main girder of the bridge. The main objective of the paper is to use the improved multi-rate fusion method to correct the monitoring data so that accurate correlation modeling of wind speed-displacement can be achieved. Two Kalman gain coefficients are introduced to improve the traditional multi-rate fusion method. The fusion method is verified by the results of simulated data analysis in time domain and frequency domain. Then, the improved multi-rate fusion method is used to fuse the monitoring lateral displacement and acceleration data of a bridge under strong wind action. The corrected lateral wind speed and displacement data is further applied to establish the correlation model through the linear regression. The improved multi-rate fusion method can overcome the inaccuracy of the high frequency stage of a Global Positioning System (GPS) sensor and the low frequency stage of acceleration sensor. The correlation coefficient of wind speed-displacement after fusion increases and the confidence interval width of regression model decreases, which indicates that the accuracy of the correlation model between wind speed and displacement is improved.
风作用是对大跨度桥梁具有显著静力和动力效应的环境作用之一。横向风速是影响桥梁主梁横向位移的主要因素。本文的主要目的是使用改进的多速率融合方法对监测数据进行校正，以便实现风速 - 位移的精确相关建模。引入两个卡尔曼增益系数以改进传统的多速率融合方法。通过时域和频域的模拟数据分析结果对该融合方法进行了验证。然后，使用改进的多速率融合方法对强风作用下一座桥梁的监测横向位移和加速度数据进行融合。将校正后的横向风速和位移数据进一步应用于通过线性回归建立相关模型。改进的多速率融合方法可以克服全球定位系统（GPS）传感器高频阶段和加速度传感器低频阶段的不准确性。融合后风速 - 位移的相关系数增大，回归模型的置信区间宽度减小，这表明风速与位移之间相关模型的精度得到了提高。
