摘要
连续梁桥建桥状态预测是保证成桥后桥梁线形流畅、平顺的重要手段。其主要内容涉及确定立模标高、挂篮变形、混凝土收缩和徐变等。其中立模标高由于受到众多因素影响往往难以准确确定,尤其是其重要组成部分预拱度更是难以预测。为解决上述问题,设计了一种新的状态预测算法,即基于并行卡尔曼滤波的递推最小二乘算法。利用上述算法预测预拱度值,进而得到立模标高。利用某桥梁对上述算法进行了仿真验证,并与直接运用卡尔曼滤波方法和最小二乘法预测结果比较,仿真结果表明,基于并行卡尔曼滤波的递推最小二乘法计算出来的预拱度值精度更高,立模标高更接近实际,建桥状态更加合理。
The paper designed a new state prediction algorithm, which is a least squares measurement algorithm based on the parallel Kalman Filter. By using this method, the pre - camber was predicted, and the mould elevation was obtained. The algorithm was simulated and verified with a bridge. And the simulation results show that, com- pared with results of Kalman Filter method and least squares measurement algorithm, the Pre - camber is more accuracy by a least squares measurement algorithm based on the parallel Kalman Filter, the mould elevation is closer to the real, and construction bridge state is more reasonable.
出处
《计算机仿真》
CSCD
北大核心
2016年第12期239-243,373,共6页
Computer Simulation
关键词
建桥状态
立模标高
预拱度
卡尔曼滤波
递推最小二乘法
仿真
Construction bridge state
Mould elevation
Pre - camber
Kalman filter
Recursive least squares
Simulation
