Research on Construction Monitoring of Continuous Rigid Frame Bridge Based on KNN Algorithm

Authors

LIU Jianlin, The First Engineering Co ., Ltd., China Railway 15th Bureau Group Co ., Ltd., Xi’an, Shaanxi 700018 , ChinaFollow
PAN Kai, The First Engineering Co ., Ltd., China Railway 15th Bureau Group Co ., Ltd., Xi’an, Shaanxi 700018 , ChinaFollow
YANG Gang, The First Engineering Co ., Ltd., China Railway 15th Bureau Group Co ., Ltd., Xi’an, Shaanxi 700018 , China
WANG Junming, School of Civil Engineering , Southwest Jiaotong University , Chengdu , Sichuan 610031 , China

Corresponding Author

潘凯，男，硕士研究生.E-mail：593292691@qq.com.

Abstract

To address common issues in bridge construction monitoring,such as sensor damage and failure in strain and displacement measurements,this study took the Nanliu Jialing River Bridge as a case and proposed a method based on the K-nearest neighbor (KNN ) algorithm to reconstruct missing construction monitoring data.ANSYS Workbench was used to establish a finite element model (FEM ) of the bridge construction process to verify the effectiveness of the KNN algorithm in the presence of missing bridge construction monitoring data.The results show:① KNN algorithm can assist in filling short-term data gaps caused by damage to strain and displacement sensors during bridge construction;② The stress at the root section of the box girder increases with the extension of the cantilever length,and the measured stress of the bottom plate is gradually close to the theoretical value.The stress at the root section of Pier 8# is larger than the theoretical value,and this error may be caused by the initial reading error of the strain gauge;③ The alignment of the main girder at Pier 8# during cantilever construction is in good agreement with expectations and gradually approaches the target line.However,the elevation of the left flange plate of the main girder section of the Qingniu side of Pier 10# is lower than the target elevation.At the same time,the elevation at the center of the top plate of the main girder section on the Hutiao side is also lower than the target,which needs timely adjustment in the subsequent construction process.

Publication Date

8-15-2025

DOI

10.14048/j.issn.1671-2579.2025.04.015

First Page

122

Last Page

129

Submission Date

August 2025

Recommended Citation

Jianlin, LIU; Kai, PAN; Gang, YANG; and Junming, WANG (2025) "Research on Construction Monitoring of Continuous Rigid Frame Bridge Based on KNN Algorithm," Journal of China & Foreign Highway: Vol. 45: Iss. 4, Article 15.
DOI: 10.14048/j.issn.1671-2579.2025.04.015
Available at: https://zwgl1980.csust.edu.cn/journal/vol45/iss4/15

Reference

[1]谭庄,勾红叶,潘凯,等.深水高墩连续刚构桥施工期流固耦合动力响应研究 [J].桥梁建设,2022,52(4):82-88.TAN Zhuang,GOU Hongye,PAN Kai,et al.Research on dynamic response of deepwater high-rise-pier continuous rigid-frame bridge during construction based on fluid-solid coupling [J].Bridge Construction,2022,52(4):82-88.
[2]杨战勇.基于温度修正徐变模型的公路大跨连续刚构桥结构状态影响分析 [J].中外公路,2021,41(4):151-156.YANG Zhanyong.Influence analysis of a highway long-span continuous rigid frame bridge based on temperature modified creep model [J].Journal of China & Foreign Highway,2021,41(4):151-156.
[3]李峰.基于数值计算和人工神经网络的桥梁施工监控技术[J].公路交通科技 (应用技术版 ),2019,15(10):132-134.LI Feng.Bridge construction monitoring technology based on numerical calculation and artificial neural network [J].Highway Traffic Technology (Applied Technology Edition ) 2019,15(10):132-134.
[4]徐建富,余毅.多跨刚构连续梁组合桥上部结构施工监控[J].世界桥梁,2011,39(4):33-35,41.XU Jianfu,YU Yi.Construction monitoring and control of superstructure of multi span rigid-frame and continuous girder hybrid bridge [J].World Bridges,2011,39(4):33-35,41.
[5]赵建.大跨度外倾式非对称系杆拱桥施工监控研究 [J].世界桥梁,2013,41(3):38-42.ZHAO Jian.Study of construction monitoring and control of long-span tied arch bridge with asymmetrical splayed arch ribs [J].World Bridges,2013,41(3):38-42.
[6]章继树.基于灰色系统理论的钢桁拱桥施工控制研究[J].世界桥梁,2016,44(4):55-58.ZHANG Jishu.Study of construction control based on grey system theory for steel truss arch bridge [J].World Bridges,2016,44(4):55-58.
[7]张永平,王润建.基于挠度监测数据的在役桥梁结构安全状态评估方法研究 [J].中外公路,2022,42(1):173-177.ZHANG Yongping,WANG Runjian.Research on structural safety assessment method of prestressed concrete continuous box girder bridge based on deflection monitoring data [J].Journal of China & Foreign Highway,2022,42(1):173-177.
[8]刘旭政,王达,许汉铮.基于线性回归的桥梁结构反应预测分析 [J].长安大学学报 (自然科学版 ),2009,29(5):76-80.LIU Xuzheng,WANG Da,XU Hanzheng.Prediction analysis of bridge structural response based on linear regression [J].Journal of Chang ’an University (Natural Science Edition ),2009,29(5):76-80.
[9]黄腾,孙泽信,李桂华,等.大跨度预应混凝土箱梁桥的挠度监测与预测 [J].工程勘察,2009,37(5):60-63,84.HUANG Teng,SUN Zexin,LI Guihua,et al.Deflection monitoring and forecasting of long span pre-stressed concrete continuous box beams [J].Geotechnical Investigation & Surveying,2009,37(5):60-63,84.
[10]曾丁,谢峻,郑晓华,等.桥梁短期实测数据修正高强混凝土收缩徐变模型与长期挠度预测 [J].公路交通科技,2014,31(11):72-77.ZENG Ding,XIE Jun,ZHENG Xiaohua,et al.Prediction of long-term deflection and correction of shrinkage and creep model of high-strength concrete of bridge based on measured short-term data [J].Journal of Highway and Transportation Research and Development,2014,31(11):72-77.
[11]姚昌荣.大跨度桥梁的施工控制理论与实践 [D].成都:西南交通大学,2004.YAO Changrong.Construction control technologies and application for long-span bridges [D].Chengdu:Southwest Jiaotong University,2004.
[12]赵丹阳.基于监测数据的大跨径斜拉桥温度效应分离与变形预测研究 [D].南京:东南大学,2019.ZHAO Danyang.Research on temperature effect separation and deformation prediction of for long-span cable-stayed bridges based on monitoring data [D].Nanjing:Southeast University,2019.
[13]陈国良,林训根,岳青,等.基于时间序列分析的桥梁长期挠度分离与预测 [J].同济大学学报 (自然科学版 ),2016,44(6):962-968.CHEN Guoliang,LIN Xungen,YUE Qing,et al.Study on separation and forecast of long-term deflection based on time series analysis [J].Journal of Tongji University (Natural Science ),2016,44(6):962-968.
[14]顾思思,常世新,韩明敏,等.毫米波雷达数据驱动的桥梁挠度预测 [J].科学技术与工程,2023,23(11):4874 -4880.GU Sisi,CHANG Shixin,HAN Mingmin,et al.Bridge deflection prediction driven by millimeter wave radar data[J].Science Technology and Engineering,2023,23(11):4874 -4880.
[15]付雷.挠度监测数据驱动 的大跨连续刚构桥安全状态分级评估方法研究 [D].重庆:重庆交通大学,2022.FU Lei.Study on graded condition assessment method of long-span continuous rigid frame bridge using deflection data[D].Chongqing:Chongqing Jiaotong University,2022.
[16]HU K J,WU X G.A bridge structure 3D representation for deep neural network and its application in frequency estimation [J].Advances in Civil Engineering,2022,2022:1999013.
[17]官治立,刘阿明.大跨度连续刚构桥托架体系设计验算[J].中外公路,2021,41(2):107-114.GUAN Zhili,LIU Aming.Design and calculation of bracket system for long-span continuous rigid frame bridges [J].Journal of China & Foreign Highway,2021,41(2):107-114.
[18]BENMAHAMED Y,TEGUAR M,BOUBAKEUR A.Application of SVM and KNN to Duval Pentagon 1 for transformer oil diagnosis [J].IEEE Transactions on Dielectrics and Electrical Insulation,2017,24(6):3443 -3451.
[19]罗向龙,李丹阳,杨彧,等.基于 KNN-LSTM 的短时交通流预测 [J].北京工业大学学报,2018,44(12):1521 -1527.LUO Xianglong,LI Danyang,YANG Yu,et al.Short-term traffic flow prediction based on KNN-LSTM [J].Journal of Beijing University of Technology,2018,44(12):1521 -1527.
[20]宋顶利,张昕,于复兴.并行优化 KNN算法的交通运输路况预测模型 [J].科技通报,2016,32(9):182-186.SONG Dingli,ZHANG Xin,YU Fuxing.Forecasting model of road transportation based on parallel optimized KNN algorithm [J].Bulletin of Science and Technology,2016,32(9):182-186.
[21]张晓利,贺国光,陆化普.基于 K-邻域非参数回归短时交通流预测方法 [J].系统工程学报,2009,24(2):178-183.ZHANG Xiaoli,HE Guoguang,LU Huapu.Short-term traffic flow forecasting based on K-nearest neighbors non-parametric regression [J].Journal of Systems Engineering,2009,24(2):178-183.
[22]中国建筑科学研究院.混凝土结构设计规范:GB 50010—2010[S].北京:中国建筑工业出版社,2011.China Academy of Building Research.Code for design of concrete structures:GB 50010—2010 [S].Beijing:China Architecture & Building Press,2011.