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山东大学学报 (工学版) ›› 2025, Vol. 55 ›› Issue (4): 127-137.doi: 10.6040/j.issn.1672-3961.0.2024.315

• 土木工程 • 上一篇    

基于GB-RAR技术的特大跨径桥梁动态变形规律监测

张国建1,付连龙1,张庆松2*,桑文刚1,李建强3,周鲁3,付涛4,刘胜震5   

  1. 1.山东建筑大学测绘地理信息学院, 山东 济南 250101;2.山东大学土建与水利学院, 山东 济南 250061;3.山东省路桥集团有限公司, 山东 济南 250013;4.山东建筑大学交通工程学院, 山东 济南 250101;5.自然资源部第一大地测量队, 陕西 西安 710054
  • 发布日期:2025-08-31
  • 作者简介:张国建(1989— ),男,山东济宁人,副教授,硕士生导师,博士,主要研究方向为工程测量与变形监测. E-mail:24155@sdjzu.edu.cn. *通信作者简介:张庆松(1970— ),男,山东费县人,教授,博士生导师,博士,主要研究方向为隧道及桥梁工程. E-mail:zhangqingsong@sdu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(52204097,42374049);山东省教育厅青年导师访学研修资助项目;山东省高等学校优秀青年创新团队资助项目(2024KJH087);山东省自然科学基金面上资助项目(ZR2022MD103);山东省大学生创新创业训练计划资助项目

Dynamic deformation law monitoring of extra-long span bridges based on GB-RAR technology

ZHANG Guojian1, FU Lianlong1, ZHANG Qingsong2*, SANG Wengang1, LI Jianqiang3, ZHOU Lu3, FU Tao4, LIU Shengzhen5   

  1. ZHANG Guojian1, FU Lianlong1, ZHANG Qingsong2*, SANG Wengang1, LI Jianqiang3, ZHOU Lu3, FU Tao4, LIU Shengzhen5(1. School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, Shandong, China;
    2. School of Civil Engineering, Shandong University, Jinan 250061, Shandong, China;
    3. Shandong Hi-Speed Road and Bridge Group Co., Ltd., Jinan 250013, Shandong, China;
    4. School of Transportation Engineering, Shandong Jianzhu University, Jinan 250101, Shandong, China;
    5. First Geodetic Survey Team, Ministry of Natural Resources, Xi'an 710054, Shaanxi, China
  • Published:2025-08-31

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摘要： 随着桥梁跨径的增大,桥梁柔性增强,桥梁动态挠度变形成为衡量桥梁是否健康运营的重要指标。传感器、测量机器人和GPS等常规监测技术由于自身的局限性,无法实现大跨径桥梁的无接触、高频和整体动态变形监测。本研究以黄河凤凰大桥为研究对象,采用GB-RAR技术监测车辆动荷载作用下的桥梁整体变形规律,并利用小波函数提升数据质量。研究成果表明,经小波去噪后,GB-RAR技术的测量中误差为0.016 5 mm,能够满足变形监测精度的要求。在车辆动荷载作用下,桥梁变形呈Wave-Sin-sqr模型演化,在跨中产生131.61 mm的最大挠度变形量,小于《公路桥涵设计通用规范》中桥梁变形容许值。本研究成果为黄河凤凰大桥等特大跨径桥梁的安全监测和加固设计提供了技术支持和数据支撑。

关键词: 地基雷达, 动荷载, 变形监测, 特大跨径桥梁

Abstract: As bridge spans increase, bridge flexibility is enhanced, making dynamic deflection deformation a critical indicator for assessing bridge health. Traditional monitoring methods, including sensors, measurement robots, and GPS, are limited in their ability to provide non-contact, high-frequency, and comprehensive dynamic deformation monitoring for large-span bridges. This research aimed to monitor the overall deformation patterns of the Yellow River Phoenix Bridge under dynamic vehicle loads using ground-based real aperture radar(GB-RAR)technology, with data quality enhanced through wavelet function analysis. The research results indicated that after wavelet denoising, the measurement error of GB-RAR was reduced to 0.016 5 mm, meeting the required accuracy for deformation monitoring. Under dynamic vehicle loads, bridge deformation followed the wave-sin-sqr model, with a maximum mid-span deflection deformation of 131.61 mm, which was within the tolerance specified by the General Codes for Highway Bridges and Culverts. These findings offered technological and data support for safety monitoring and reinforcement design of ultra-large-span bridges, such as the Yellow River Phoenix Bridge.

Key words: ground-based radar, dynamic load, deformation monitoring, ultra-large-span bridge

中图分类号: 

  • P237
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