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基于GUM-RF协同模型的悬索桥吊索加工长度不确定性控制研究
基金项目(Foundation): 国家自然科学基金(12272135); 中国国家铁路集团有限公司科技研究开发计划(K2023G038)
邮箱(Email): 871634343@qq.com
DOI:
发布时间: 2026-09-11
出版时间: 2026-09-11
网络发布时间: 2026-09-11
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摘要:

现行规范对悬索桥吊索加工长度提出±2 mm的严苛制造精度要求,但测量过程存在显著不确定度,导致传统判定方法难以客观评价测量可靠性。针对这一问题,本文基于测量不确定度表示指南(GUM)框架,建立涵盖12项输入变量的吊索长度测量不确定度评定模型,并引入随机森林(RF)算法对影响因素进行重要性排序,筛选出测力、测距、测温3项关键能力变量。据此提出“分而治之”控制策略:对关键变量实施精度强化控制,对非关键因素仅维持现行规范质量稳定性要求,并构建仅依赖设计长度与设计荷载的简化预测模型(调整决定系数R2=0.974,预测平均绝对偏差0.01 mm)。以五峰山长江大桥为工程实例,全桥312根吊索加工长度的测量不确定度均控制在1.09 mm以内,制造误差低于2 mm,实现免调索安装,并借助同步张拉仅以48次作业完成全部测量。结果表明,该协同模型可有效量化与控制吊索长度不确定度,为现行标准引入测量不确定度评估提供了可操作的实现路径,并为大跨铁路悬索桥的高精度制造与施工控制提供理论支撑。

Abstract:

Current standards impose a stringent manufacturing accuracy requirement of ±2 mm for the suspender fabrication length of suspension bridges, yet the measurement involves significant uncertainty, making it difficult for traditional methods to objectively assess measurement reliability. To address this issue, this study establishes a measurement uncertainty evaluation model for suspender based on the Guide to the Expression of Uncertainty in Measurement (GUM) framework, incorporating 12 input variables. The Random Forest (RF) algorithm is introduced to rank the importance of influencing factors, thereby identifying three key capability variables: force measurement, distance measurement, and temperature measurement. Accordingly, a “divide and conquer” control strategy is proposed: enhanced precision control is applied to the critical variables, while only the current quality stability requirements of the specifications are maintained for non critical factors. A simplified prediction model relying solely on design length and design load is constructed, achieving an adjusted coefficient of determination R2=0.974 and a mean absolute deviation of prediction of 0.01 mm. Taking the Wufengshan Yangtze River Bridge as an engineering example, the measurement uncertainties for the fabricated lengths of all 312 suspenders are controlled within 1.09 mm, and the manufacturing errors are below 2 mm, enabling "adjustment-free" installation, synchronous tensioning further completes all measurements in only 48 operations.. The results demonstrate that this collaborative model can effectively quantify and control the length uncertainty of suspenders, providing a practicable implementation path for introducing measurement uncertainty evaluation into current standards, and offering theoretical support for the high precision manufacturing and construction control of long span railway suspension bridges.

参考文献

[1]唐贺强,徐恭义,刘汉顺.五峰山长江大桥主桥总体设计[J].桥梁建设,2020,50(6):1-7.

[2]张太科,唐茂林,董江华,等.超大跨度四缆悬索桥施工控制关键问题研究[J].现代交通与冶金材料,2025,5(6):72-81.

[3]冯广胜.五峰山长江大桥钢梁架设与线形控制技术[J].中国铁路,2021(9):139-146.

[4] Wang Z P, Zhang We M, Wang Z W. Analytical assessment of the effects of multicategory errors on the completed state of a suspension bridge: Stepwise multiple regression analysis and FEM validation[J].2026,31(4): 04026007.

[5]张士轩,石艺歌.两端销接式吊索索长控制技术[J].世界桥梁,2021,49(5):41-46.

[6] Kacker R. An interpretation of the guide to the expression of uncertainty in measurement: NIST SP 500-244[R]. Gaithersburg, MD: National Institute of Standards and Technology, 2000.

[7] Kessel W. Measurement uncertainty according to ISO/BIPM-GUM[J]. Thermochimica Acta, 2002, 382:1-16.

[8]靳浩元,刘军.测量不确定度的评定方法及应用研究[J].计量科学与技术,2021,65(5):124-131.

[9]张子安,张永强,丁明理.对深度学习中目标定位不确定度评定的讨论[J].测控技术,2024,43(3):1-8.

[10] Wang Y L, Sang Y, Xu J. Indoor positioning based on kernel function and analysis of measurement uncertainty[C]. IOP Conference Series: Materials Science and Engineering, 2019, 490: 062070.

[11] 付百学,胡胜海,袁纲.汽车超声波油耗仪测试结果的不确定度评定[J].中国公路学报,2014,27(4):121-126.

[12] Díaz-Pérez Lc, Torralba M, Muro L, et al. Uncertainty budget of a large-range nanopositioning platform based on Monte Carlo simulation[J]. Measurement, 2023,208:112469.

[13]田元.斜拉桥索力测量不确定度影响因素初步研究[D]. 重庆:重庆交通大学,2015.

[14] Chen R C, Cui S, Khoo D, et al. Modelling and quantification of measurement uncertainty for leak localisation in a gas pipeline[J]. Measurement: Sensors, 2022, 24: 100443.

[15] Gimsing N J, Georgakis C T. Cable supported bridges: concept and design [M]. 3rd Edition. Chichester: Wiley, 2012.

[16] Breiman L. Random forests[J]. Machine Learning, 2001, 45(1): 5-32. DOI∶10.1023/A∶1010933404324.

[17]曾笑奇,赵秋皓,冯友建.基于可解释性机器学习的养老产业空间布局研究:以杭州市为例[J].浙江大学学报(理学版),2025,52(3):289-299.

[18]刘文硕,钟明锋,周博,等.基于机器学习的高速铁路斜拉桥钢箱梁温度模式研究[J].华南理工大学学报(自然科学版),2025,53(6):25-33.

[19]李冰.五峰山长江大桥缆索系统施工控制技术[J].桥梁建设,2021,51(4):119–126.

[20]冯传宝.五峰山长江大桥上部结构施工控制技术[J].桥梁建设,2020,50(1):99-104.

[21]谭社会,张雨潇,周丽,等.基于温度变形的五峰山长江大桥轨道线形调控方法[J].铁道科学与工程学报,2024,21(10):4076-4088.

基本信息:

中图分类号:U448.25;U445.47

引用信息:

[1]王俊芳,孙新喜,申建伟.基于GUM-RF协同模型的悬索桥吊索加工长度不确定性控制研究[J].铁道建筑().

基金信息:

国家自然科学基金(12272135); 中国国家铁路集团有限公司科技研究开发计划(K2023G038)

发布时间:

2026-09-11

出版时间:

2026-09-11

网络发布时间:

2026-09-11

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