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基于加速度传感器的检定轻墩铁路桥梁横向位移新方法及振动台试验验证

陈令坤, 徐祥, 蒋丽忠, 张清华, 张楠, 李乔

陈令坤, 徐祥, 蒋丽忠, 张清华, 张楠, 李乔. 基于加速度传感器的检定轻墩铁路桥梁横向位移新方法及振动台试验验证[J]. 工程力学, 2022, 39(4): 76-85. DOI: 10.6052/j.issn.1000-4750.2021.02.0144
引用本文: 陈令坤, 徐祥, 蒋丽忠, 张清华, 张楠, 李乔. 基于加速度传感器的检定轻墩铁路桥梁横向位移新方法及振动台试验验证[J]. 工程力学, 2022, 39(4): 76-85. DOI: 10.6052/j.issn.1000-4750.2021.02.0144
CHEN Ling-kun, XU Xiang, JIANG Li-zhong, ZHANG Qing-hua, ZHANG Nan, LI Qiao. A NOVEL ACCELEROMETER-BASED METHOD FOR ESTIMATING THE TRANSVERSE DISPLACEMENT OF LIGHT PIER RAILROAD BRIDGES AND SHAKING TABLE TEST VERIFICATION[J]. Engineering Mechanics, 2022, 39(4): 76-85. DOI: 10.6052/j.issn.1000-4750.2021.02.0144
Citation: CHEN Ling-kun, XU Xiang, JIANG Li-zhong, ZHANG Qing-hua, ZHANG Nan, LI Qiao. A NOVEL ACCELEROMETER-BASED METHOD FOR ESTIMATING THE TRANSVERSE DISPLACEMENT OF LIGHT PIER RAILROAD BRIDGES AND SHAKING TABLE TEST VERIFICATION[J]. Engineering Mechanics, 2022, 39(4): 76-85. DOI: 10.6052/j.issn.1000-4750.2021.02.0144

基于加速度传感器的检定轻墩铁路桥梁横向位移新方法及振动台试验验证

基金项目: 2018年度江苏省建设系统科技项目——江苏省防灾减灾抗震“四新”技术专题研究项目(2018ZD039);高速铁路基础研究联合基金项目(U1934207);轨道交通安全教育部重点实验室2019年开放基金项目(2019JZZ01);湖南创新型省份建设专项经费资助项目(2019RS3009);国家自然科学基金项目(5177863,51878561,51778533);湖南创新型省份建设专项项目(2019RS3009);中南大学创新驱动项目(502501006)
详细信息
    作者简介:

    徐 祥(1994−),男,江苏人,硕士生,从事桥梁智能健康监测研究 (E-mail: MX120180447@yzu.edu.cn)

    蒋丽忠(1971−),男,湖南人,教授,博士,博导,长江学者,院长,从事工程结构抗震方面的研究 (E-mail: lzhjiang@csu.edu.cn)

    张清华(1975−),男,河南人,教授,工学博士,博导,副系主任,从事高性能桥梁新结构设计理论研究(E-mail: swjtuzqh@126.com)

    张 楠(1971−),男,山东人,教授,博士,博导,从事车桥耦合振动研究 (E-mail: nzhang@bjtu.edu.cn)

    李 乔(1954−),男,黑龙江人,教授,博士,从事桥梁结构分析与抗震研究(E-mail: civillq@swjtu.edu.cn)

    通讯作者:

    陈令坤(1974−),男,安徽人,副教授,博士,硕导,研究所主任,从事车桥耦合振动研究 (E-mail: lkchen@yzu.edu.cn)

  • 中图分类号: U448.13

A NOVEL ACCELEROMETER-BASED METHOD FOR ESTIMATING THE TRANSVERSE DISPLACEMENT OF LIGHT PIER RAILROAD BRIDGES AND SHAKING TABLE TEST VERIFICATION

  • 摘要: 截至2019年,全国铁路完成货物发送量43.89亿吨,且货运量年增长率保持在9%~10%。既有线路有很大比例的早期建设的轻型桥墩桥梁,由于其横向刚度较弱,在运营过程中常常出现横向位移较大的现象。随着既有线提速及货运量的增加,这一现象愈加明显。铁路运营期间,为防止列车脱轨,对于该类桥梁的位移变形的要求较高。因此需要一种能够适应恶劣的环境条件,可以实时持续可靠地监测桥梁位移的方法。当前测量桥梁位移的方法,通常基于昂贵的设备和复杂的模型,并且局限于良好的天气条件并不能满足在有限的成本下对桥梁进行持续高效的维护。该文提出一种基于加速度传感器的检定轻墩铁路桥梁横向位移的监测方法。其特点是,依靠低成本易操作的加速度传感器对桥梁高频动态位移和低频伪静态位移进行持续准确的监测检定,而不需要依靠良好的天气环境和架设条件。该研究设计一种巧妙的振动台试验,通过一系列的试验对该方法进行了验证。试验结果表明:加速度传感器能够准确的检定位移,与线性随动位移计相比,最大峰值误差只有11.80%,最大均值位移误差只有8.05%。
    Abstract: As of 2019, the nation's railroads have delivered a total of 4.38 billion tons of freight. A significant number of current piers are light piers built earlier, and are often deflected due to their limited lateral stiffness. The deflection of piers is getting increasingly evident as the line speeds up and freight increases. On the other hand, the railroad requires a high deformity of train tracks to avoid derailment. Hence, a method is in need that can monitor the track displacement in harsh environments timely and continuously. Current methods depend on costly machines and accurate models which are available only under good weather conditions. It presents a technique to track the lateral movement of light piers with accelerometers. It utilizes low-cost and easy-to-mount accelerometers for persistent and reliable detection of high-dynamic and low-frequency pseudo-static displacements. A novel shaking table is built and the concept is proven by numerical experiments. Compared with the linear follower displacement meter, the peak error is 11.80% and the mean error is 8.05%.
  • 图  1   双轴的传感器转角

    Figure  1.   Double axis sensor corner

    图  2   结构简图

    Figure  2.   Structure calculation principle sketch

    图  3   总位移检定图

    Figure  3.   Total displacement estimation

    图  4   Model3711E1110G直流响应加速度计

    Figure  4.   Model3711E1110G DC responsive accelerometer

    图  5   线性可变差动变压器(LVDT)

    Figure  5.   Linear variable differential transformer

    图  6   试验整体设置

    Figure  6.   Overall experimental setup

    图  7   激励位移时程曲线对比

    Figure  7.   Comparison of excitation displacement time history curves

    图  8   位移对比图

    Figure  8.   Displacement comparison

    表  1   Model 3711E1110G直流加速度计性能参数

    Table  1   Model 3711E1110G DC accelerometer performance parameters

    性能描述
    灵敏度(±5%) 200 mV/g (20.4 mV/(m/s2))
    测量范围±10 g (±98.1 m/s2 峰值)
    宽带分辨率(0.5 Hz~100 Hz) 0.2 mg均方根加速度
    (0.002 m/s2均方根加速度)
    温度范围(工作温度范围) −65℉ ~ +250℉ (−54.0 ℃ ~ +121 ℃)
    频率范围(±3 dB) 0 Hz~1000 Hz
    电源接口4针
    下载: 导出CSV

    表  2   线性可变差动变压器(LVDT)性能参数

    Table  2   Linear variable differential transformer (LVDT) performance parameters

    性能描述
    电压14 V~26 V, 30 mA
    输出0 V~10 V (负满量程)
    输出荷载2 k Ohms
    输出波动30 mV (峰值对峰值)
    电输出带宽200 Hz
    输出阻抗2 Ohms
    温度系数±0.017% F.S./ ℉ (正常环境)
    工作温度范围−40℉~158℉
    电终端6.6 ft (电缆总长)
    下载: 导出CSV

    表  3   10组位移时程数据

    Table  3   10 sets of displacement time history data

    列车方向时间/s正总峰值
    位移/mm
    负总峰值
    位移/mm
    正动峰值
    位移/mm
    负动峰值
    位移/mm
    正静峰值
    位移/mm
    负静峰值
    位移/mm
    列车速度/
    (km/h)
    1SB74.231.550−6.2723.975−3.9010.520−4.2958.7
    2NB73.072.627−6.5093.612−3.5490.526−2.9678.7
    3SB33.751.300−8.3214.141−3.8050.009−5.13416.2
    4NB32.944.071−8.2075.140−5.0460.058−4.25417.8
    5SB24.624.968−7.1326.423−4.1841.323−4.30223.3
    6NB19.869.851−11.05511.406−7.7720.018−5.35624.9
    7SB28.224.870−8.1146.779−5.5260.938−3.10633.9
    8NB15.9113.698−13.37813.310−9.7800.445−5.60331.1
    9SB13.365.656−12.4415.892−5.0931.164−7.94241.5
    10NB11.2913.925−12.32010.467−7.0893.880−5.08941.0
    下载: 导出CSV

    表  4   10组检定位移时程曲线峰值位移误差E1数据

    Table  4   Peak displacement error E1 of 10 sets of estimated displacement time history curves

    E1/(%)1组2组3组4组5组6组7组8组9组10组平均
    动态位移0.5026.6114.7415.5515.7222.0713.0820.1115.0519.6016.30
    伪静态位移6.2211.783.679.826.3716.374.7014.683.599.508.67
    总位移2.414.532.615.088.2011.809.446.673.710.085.45
    下载: 导出CSV

    表  5   10组检定位移时程曲线均方根位移误差E2数据

    Table  5   RMS displacement error E2 of 10 group estimated displacement time-course curve

    E2/(%)1组2组3组4组5组6组7组8组9组10组平均
    动态位移4.895.396.815.964.595.415.235.266.575.355.55
    伪静态位移3.873.984.374.5311.3711.3418.1814.427.4519.609.91
    总位移3.613.993.824.307.856.568.056.434.385.715.47
    下载: 导出CSV
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  • 收稿日期:  2021-02-20
  • 修回日期:  2021-05-31
  • 网络出版日期:  2021-07-05
  • 刊出日期:  2022-03-24

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