预应力混凝土梁桥短线匹配法的抗差估计方法
Robust estimation method for short-line matching method of prestressed concrete beam bridges
孟俊苗 1贾菁林 1刘永健 1刘江 1霰建平 2肖军2
作者信息
- 1. 长安大学 公路学院,陕西 西安 710064;长安大学 陕西省"四主体一联合"桥梁工程智能建造技术校企联合研究中心,陕西 西安 710064
- 2. 长安大学 陕西省"四主体一联合"桥梁工程智能建造技术校企联合研究中心,陕西 西安 710064;中交第二公路工程局有限公司,陕西 西安 710065
- 折叠
摘要
针对预应力混凝土梁桥短线匹配法线形控制问题,充分考虑节段梁控制点测量值中可能出现的随机误差与粗差,提出一种附有条件限制的总体最小二乘抗差估计方法,适用于短线匹配法线形控制;推导了解算方法,并给出了具体的解算步骤;以黄茅海跨海通道工程 6×60 m连续刚构中的某一跨为基准进行了数据模拟.结果表明:该方法可以实时地修正施工中各类误差导致的预制线形变化,有效地阻止了施工误差与测量误差在后续节段梁中的不断积累;与既有算法相比,所提算法的计算结果准确度最高,不仅在终端节段末端与基准线形的差值均值最小,而且在代表整体线形连续性的偏差平方和均值上与最小二乘法的结果相近,优于传统的选点控制方法.
Abstract
Aiming to the alignment control of prestressed concrete beam bridges prefabricated by short-line matching method,considering the possible random errors and gross errors in the measured values of segmental beam control points,a total least square robust estimation method with constraints was proposed,which was suitable for the alignment control of short-line matching method.The solution method was derived and the specific steps were given.A certain span of a 6×60 m continuous rigid frame in Huangmaohai sea-crossing channel project was used as the reference for data simulation.The results show that the method can correct the error of the prefabrication alignment caused by various errors during construction process in real time,and effectively prevent the accumulation of construction errors and measurement errors in subsequent segmental beams.The comparison with the existing algorithms shows that the accuracy of the proposed algorithm is the highest.The mean difference between the end of the terminal segment and the reference alignment is the smallest.Moreover,the mean square sum of the deviations representing the continuity of the general alignment is similar to the result of the least square method,which is better than the traditional point selection control method.
关键词
装配式梁桥/抗差估计/总体最小二乘法/短线匹配法/坐标转换Key words
prefabricated beam bridge/robust estimation/total least square method/short-line matching method/coordinate transformation引用本文复制引用
出版年
2024
NETL
NSTL
万方数据