Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (1): 188-197.doi: 10.13229/j.cnki.jdxbgxb.20230135

Previous Articles    

Bridge weigh-in-motion combined with machine version

Guan-xu LONG1,2(),Xiu-shi ZHANG3,Gong-feng XIN1,2,Tao WANG3(),Gan YANG3   

  1. 1.Innovation Research Institute，Shandong Hi-Speed Group Co. ，Ltd. ，Jinan 250101，China
    2.School of Highway，Chang'an University Xi'an 710064，China
    3.Shandong Key Laboratory of Highway Technology and Safety Assessment，Jinan 250101，China
  • Received:2023-02-16 Online:2024-01-30 Published:2024-03-28
  • Contact: Tao WANG E-mail:longgx5@163.com;wtbridge@chd.edu.cn

RICH HTML

 2   

PDF (PC)

127

Abstract:

To further improve the existing bridge weigh-in-motion technique， this paper proposes a bridge weigh-in-motion system integrated with machine vision. Firstly， the machine vision algorithm is used to identify and track the vehicle； then， the bridge response monitoring information under the action of the vehicle is processed； furthermore， the axle load and axle base are identified by using the virtual simply-supported beam theory； finally， the method is tested by simulation and test. The results show that the method proposed in this paper has a good identification effect on the axle weight and wheelbase of vehicles under various working conditions. The average relative errors of the identification of axle weight， wheelbase and total weight are 3.40%， 4.31% and 2.71% respectively. It has a certain anti-noise ability， which shows that the method has good robustness and applicability.

Key words: bridge engineering, bridge weigh-in-motion, machine vision, virtual simply-supported beam

CLC Number: 

  • U446.2

Fig.1

Framework of novel bridge weigh-in-motion approach"

Fig.2

Vehicle recognition effect"

Fig.3

Coordinate system transformation relation"

Fig.4

Schematics of virtual simply-supported beam method"

Fig.5

Diagram of wheelbase indentification"

Fig.6

Typical cross section（cm）"

Fig.7

Arrangement of measuring points"

Fig.8

Finite element model diagram"

Table 1

Vehicle model parameter information table"

参数两轴车三轴车
车辆总重G/t16.219.6
车体质量Mv /t12.415.7
车体点头惯性矩Jyv /（kg·m2）21 670172 000
车体侧翻惯性矩Jxv /（kg·m2）5 30061 500
第1轴轴重MA1/t6.25.5
第2轴轴重MA2/t1010
第3轴轴重MA3/t-4.1
第1轴到车体重心水平距离L1/m3.74.84
第2轴到车体重心水平距离L2/m2.31.51
第3轴到车体重心水平距离L3/m-2.81

Fig.9

Identification errors under different speeds"

Fig.10

Identification errors under different RSCs"

Fig.11

Identification errors under different noise levels"

Table 2

Multi-vehicle load conditions"

工况编号加载车辆 模型加载 车道加载速度/（m·s-1）车头时 距/s
S111100.4
2210
S211100.8
2210
S311101.2
2210

Table 3

Multi-vehicle driving conditions recognition error statistics table"

工况识别参数二轴车三轴车
实际识别误差/%实际识别误差/%
S1AW1/t6.206.170.445.505.561.04
AW2/t10.009.851.5110.009.514.85
AW3/t---4.104.325.39
G/t16.2016.020.445.505.561.04
D1/m6.006.274.506.356.878.19
D2/m---1.301.0717.69
S2AW1/t6.206.271.085.505.293.77
AW2/t10.009.920.7810.0010.222.19
AW3/t---4.103.943.99
G/t16.2016.190.0719.619.450.77
D1/m6.006.183.006.356.685.20
S3D2/m---1.301.1513.04
AW1/t6.206.260.985.505.500.09
AW2/t10.009.980.1910.009.841.57
AW3/t---4.104.222.90
G/t16.2016.240.2619.6019.570.17
D1/m6.006.101.676.356.492.20
D2/m---1.301.254.00

Fig.12

Test platform"

Table 4

Vehicle model wheelbase and axle load parameters table"

参数1号车辆 模型2号车辆 模型3号车辆 模型
轴距D/m0.410.7550.755
第1轴轴重AW1/kg1517.822
第2轴轴重AW2/kg1517.822
总重G/kg3035.644

Fig.13

Arrangement of strain sensors（cm）"

Fig.14

Measured dynamic response of strain sensor"

Fig.15

Result of test car"

Table 5

Cycling test conditions table"

工况编号加载车辆模型加载车道加载速度/（m·s-1）

S1

S2

1号车10.3
1号车10.5

S3

S4

1号车10.7
2号车10.3

S5

S6

2号车10.5
2号车10.7

Fig.16

Cycling conditions recognition error statistical figure"

Table 6

Multi-vehicle test conditions table"

工况编号加载车辆模型加载车道加载速度/（m·s-1）车头时距/s
S7110.34
320.3
S8110.38
320.3
S9110.312
320.3

Fig.17

Multi-vehicle conditions recognition error statistical figure"

1 何维. 公路桥梁动态称重关键技术研究[D]. 长沙:湖南大学土木工程学院, 2019.
He Wei. Study of key technologies for highway bridge weigh-in-motion[D]. Changsha: College of Civil Engineering,Hunan University, 2019.
2 任伟新, 左小晗, 王宁波, 等. 非路面式桥梁动态称重研究综述[J]. 中国公路学报, 2014, 27(7): 45-53.
Ren Wei-xin, Zuo Xiao-han, Wang Ning-bo, et al. Review of non-pavement bridge weigh-in-motion[J]. China Journal of Highway and Transport, 2014, 27(7): 45-53.
3 Moses F. Weigh-in-motion system using instrumented bridges[J]. Journal of Transportation Engineering, 1979, 105(3): 233-249.
4 O'Brien E J, Quilligan M J, Karoumi R. Calculating an influence line from direct measurements[J]. Bridge Engineering, 2006, 159(1): 31-34.
5 邓露, 施海, 何维, 等. 基于虚拟简支梁法的桥梁动态称重研究[J]. 振动与冲击, 2018, 37(15): 209-215.
Deng Lu, Shi Hai, He Wei,et al. Vehicles' BWIM based on virtual simply-supported beam method[J]. Journal of Vibration and Shock,2018,37(15):209-215.
6 施海. 基于虚拟简支梁法的桥梁动态称重研究[D]. 长沙:湖南大学土木工程学院, 2017.
Shi Hai. Bridge weigh-in-motion based on the virtual simply-supported beam method[D]. Changsha: College of Civil Engineering,Hunan University, 2017.
7 Deng L, He W, Yu Y, et al. Equivalent shear force method for detecting the speed and axles of moving vehicles on bridges [J]. Journal of Bridge Engineering, 2018, 23(8): No.04018057.
8 He W, Deng L, Shi H, et al. Novel virtual simply supported beam method for detecting the speed and axles of moving vehicles on bridges[J]. Journal of Bridge Engineering, 2016, 22(4): No.04016141.
9 韩万水, 李彦伟, 乔磊, 等. 基于车-桥耦合振动理论的移动荷载识别[J]. 中国公路学报, 2013, 26(1): 74-86.
Han Wan-shui, Li Yan-wei, Qiao Lei, et al. Moving load identification based on vehicle bridge coupling vibration theory[J]. China Journal of Highway and Transport, 2013, 26(1): 74-86.
10 张青霞. 基于虚拟变形法的动态荷载与结构损伤识别方法研究[D]. 哈尔滨: 哈尔滨工业大学土木工程学院, 2010.
Zhang Qing-xia. Dynamic load and structural damage identification using virtual distortion method[D]. Harbin: School of Civil Engineering,Harbin Institute of Technology,2010.
11 Yang G, Wang P, Han W S, et al. Automatic generation of fine-grained traffic load spectrum via fusion of weigh-in-motion and vehicle spatial-temporal information[J]. Computer-aided Civil and Infrastructure Engineering, 2022, 37(4):485-499.
12 夏烨, 简旭东, 邓露, 等. 交通视频辅助的桥梁动态称重方法研究[J]. 中国公路学报, 2021, 34(12): 104-114.
Xia Ye, Jian Xu-Dong, Deng Lu, et al. Research on traffic-video-aided bridge weigh-in-motion approach[J]. China Journal of Highway and Transport,2021, 34(12):104-114.
13 余婷. 基于影响线的桥梁快速安全评定方法研究[D]. 南京: 东南大学土木工程学院, 2019.
Yu Ting. Rapid assessment method of bridge safety condition based on influence line[D]. Nanjing: School of Civil Engineering,Southeast University, 2019.
14 Lecun Y, Bottou L, Bengio Y, et al. Gradient-based learning applied to document recognition[J]. Proceedings of IEEE, 1998, 86(11):2278-2324.
15 Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[C]∥ International Conference on Neural Information Processing Systems, Lake Tahoe, USA,2012:1097-1105.
16 Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[J/OL]. arXiv e-prints, 2014.
17 Girshick R B, Donahue J, Darrell T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]∥IEEE Conference on Computer Vision and Pattern Recognition, Columbus,USA, 2014: 580-587.
18 Girshick R. Fast RCNN[C]∥IEEE International Conference on Computer Vision, Cambridge, USA, 2015: 1440-1448.
19 Redmon J, Farhadi A.YOLOv3: An incremental improvement[J/OL].[2018-12-10]. .
20 杨干, 韩万水, 张书颖. 基于多源信息融合的交通荷载重构方法研究[C]∥世界交通运输大会论文集, 中国,武汉,2022: 421-426.
Yang Gan, Han Wan-shui, Zhang Shu-ying. Research on traffic load reconstruction method based on multi-source information fusion[C]∥Proceedings of 2022 World Transport Convention, Wuhan, China, 2022: 421-426.
21 韩万水, 陈艾荣. 随机车流下的风-汽车-桥梁系统空间耦合振动研究[J]. 土木工程学报, 2008(9):97-102.
Han Wan-shui, Chen Ai-rong. Three-dimensional coupling vibration of wind-vehicle-bridge systems under random traffic flow[J]. China Civil Engineering Journal,2008(9):97-102.
22 韩万水, 马麟, 汪炳, 等. 随机车流-桥梁系统耦合振动精细化分析与动态可视化[J]. 中国公路学报, 2013, 26(4):78-87.
Han Wan-shui, Ma Lin, Wang Bing, et al. Refinement analysis and dynamic visualization of traffic-bridge coupling vibration system[J]. China Journal of Highway and Transport,2013,26(4):78-87.
23 邓露, 何维, 俞扬, 等. 公路车-桥耦合振动的理论和应用研究进展[J]. 中国公路学报, 2018, 31(7):38-54.
Deng Lu, He Wei, Yu Yang, et al. Research progress in theory and applications of highway vehicle-bridge coupling vibration[J]. China Journal of Highway and Transport, 2018,31(7):38-54.
24 . Mechanical vibration-road surface profiles-reporting of measured data [S].
[1] Guo-jin TAN,Ji OU,Yong-ming AI,Run-chao YANG. Bridge crack image segmentation method based on improved DeepLabv3+ model [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(1): 173-179.
[2] Ran AN,You-zhi WANG. Shear properties of shear stud connectors under combined tension and shear loading [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(9): 2554-2562.
[3] Xin-dai ZUO,Jin-quan ZHANG,Shang-chuan ZHAO. Fatigue stiffness degradation and life prediction method of in⁃service concrete T⁃beams [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(9): 2563-2572.
[4] Zheng-wei GU,Pan ZHANG,Dong-ye LYU,Chun-li WU,Zhong YANG,Guo-jin TAN,Xiao-ming HUANG. Earthquake⁃induced residual displacement analysis of simply supported beam bridge based on numerical simulation [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1711-1718.
[5] Chun-li WU,Shi-ming HUANG,Kui LI,Zheng-wei GU,Xiao-ming HUANG,Bing-tao ZHANG,Run-chao YANG. Analysis of pier action effect under flood based on numerical simulation and statistical analysis [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1612-1620.
[6] Guo-jin TAN,Qing-wen KONG,Xin HE,Pan ZHANG,Run-chao YANG,Yang-jun CHAO,Zhong YANG. Bridge scour depth identification based on dynamic characteristics and improved particle swarm optimization algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1592-1600.
[7] Hui JIANG,Xin LI,Xiao-yu BAI. Review on development of bridge seismic structural systems： from ductility to resilience [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1550-1565.
[8] Feng WANG,Shuang-rui LIU,Jia-ying WANG,Jia-ling SONG,Jun WANG,Jiu-peng ZHANG,Xiao-ming HUANG. Size and shape effects of wind drag coefficients for porous structures [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1677-1685.
[9] Jun WANG,Jia-wu LI,Feng WANG,Jiu-peng ZHANG,Xiao-ming HUANG. Wind speed distribution in simplified U⁃shaped valley and its effect on buffeting response of long⁃span suspension bridge [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1658-1668.
[10] Hua WANG,Long-lin WANG,Zi-mo ZHANG,Xin HE. Safety early warning technology of continuous rigid frame bridges based on crack width variation [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1650-1657.
[11] Yu FENG,Jian-ming HAO,Feng WANF,Jiu-peng ZHANG,Xiao-ming HUANG. Analysis of transient wind⁃induced response of long⁃span bridge under nonstationary wind field [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1638-1649.
[12] Ye YUAN. Natural frequency analysis of beam bridge structure under temperature and vehicle action [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1702-1710.
[13] Zi-yu LIU,Shi-tong CHEN,Mo-mo ZHI,Xiao-ming HUANG,Zhe-xin CHEN. Ultimate bearing capacity of temporary⁃permanent conversion rush⁃repair steel pier for emergency use [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(6): 1601-1611.
[14] Yue ZHANG,Chuan-sen LIU,Fei SONG. Influence of abutment back wall on continuous girder bridge's seismic fragility [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(5): 1372-1380.
[15] Shu-wei LAN,Dong-hua ZHOU,Xu CHEN,Nan-ming MO. Practical calculation method for the critical bearing capacity of double column bridge with high piers [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(4): 1105-1111.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd