|Table of Contents|

Laser ranging self-calibration method and system used for image measurement of fatigue cracks in steel bridge decks(PDF)

长安大学学报(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2025年01期
Page:
60-68
Research Field:
桥梁与隧道工程
Publishing date:

Info

Title:
Laser ranging self-calibration method and system used for image measurement of fatigue cracks in steel bridge decks
Author(s):
HUANG Bin CHENG Bin ZHOU Huan-xin ZENG Ling-bo
(School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)
Keywords:
bridge engineering fatigue crack image measurement laser ranging steel bridge deck self-calibration method
PACS:
U446
DOI:
10.19721/j.cnki.1671-8879.2025.01.006
Abstract:
Image measurement is an efficient method to detect the fatigue cracks in steel bridge decks, while it is inconvenient to set calibration targets and auxiliary devices or to place the cameras in special poses during the image calibration process, and as a result high-precision, real-time, and dynamic calibration cannot be achieved. To address the above problems, a laser ranging self-calibration method used for the image measurement of fatigue cracks in steel bridge decks was proposed. This method employs high-precision laser rangefinders to synchronously measure the position of the steel plate surface when taking the crack pictures, so that the object plane equation can be determined. Then the 2D coordinates of four sets of points that have been selected respectively from the object plane and the image planes can be obtained, and the homography matrix which represents the mapping relationship between object and image planes can be solved, so that the real-time calibration can be completed simply and rapidly. A set of image measurement system for fatigue cracks in steel bridge decks based on laser ranging self-calibration was independently developed, and the accuracy verification of self-calibration image measurement was carried out in the typical areas of the steel bridge deck. Furthermore, the image measurement of fatigue cracks in the steel bridge deck was conducted. The image feature points of fatigue cracks were extracted by using image processing methods such as grayscale conversion, erosion and dilation, filtering and denoising, binarization, extraction of connected components and medial axis transformation. Combined with the calibration results, the size measurement of various cracks with irregular shapes was realized. The results show that in the accuracy verification of self-calibration image measurement, the measurement relative errors of the ruler's length in the typical areas are all within 0.23%, which indicates that the laser ranging self-calibration method is accurate and robust. In the image measurement of fatigue cracks in the steel bridge decks, the measured values of crack sizes are relatively close to the actual values, and the measurement relative errors are all within 1.35%, providing a reference for the application of this method and system in real engineering.2 tabs, 12 figs, 25 refs.

References:

[1] 张清华,崔 闯,卜一之,等.港珠澳大桥正交异性钢桥面板疲劳特性研究[J].土木工程学报,2014,47(9):110-119.
ZHANG Qing-hua,CUI Chuang,BU Yi-zhi,et al.Study on fatigue features of orthotropic decks in steel box girder of Hong Kong-Zhuhai-Macao bridge[J].China Civil Engineering Journal,2014,47(9):110-119.
[2]CHENG B,YE H,CAO X,et al.Experimental study on fatigue failure of rib-to-deck welded connections in orthotropic steel bridge decks[J].International Journal of Fatigue,2017,103:157-167.
[3]张鹏飞,殷志欢,常 军.复杂应力耦合作用下斜拉桥正交异性桥面板疲劳断裂[J].长安大学学报(自然科学版),2021,41(4):78-89.
ZHANG Peng-fei,YIN Zhi-huan,CHANG Jun.Fatigue fracture of orthotropic steel deck of cable-stayed bridge under complex coupling stress[J].Journal of Chang'an University(Natural Science Edition),2021,41(4):78-89.
[4]程 斌,石林泽,刘天成.基于Lamb导波深度学习的钢桥面板疲劳裂纹智能监测研究[J].中国公路学报,2023,36(2):120-128.
CHENG Bin,SHI Lin-ze,LIU Tian-cheng.Research on intelligent monitoring of fatigue cracks in steel bridge decks based on deep learning of lamb guided waves[J].China Journal of Highway and Transport,2023,36(2):120-128.
[5]NUNEZ I,NEGRIERA C A.Efficiency parameters in time reversal acoustics:Applications to dispersive media and multimode wave propagation[J].Journal of the Acoustical Society of America,2005,117(3):1202-1209.
[6]PARK G S,PARK E S.Improvement of the sensor system in magnetic flux leakage-type nondestructive testing(NDT)[J].Transaction on Magnetics,2002,(3):56-62.
[7]GOKTEPE M.Non-destructive crack detection by capturing local flux leakage field[J].Sensors and Actuators,2001(3):75-78.
[8]马亚飞,孙文康,何 羽,等.基于DC-Unet的混凝土桥梁表观裂缝识别方法[J].长安大学学报(自然科学版),2024,44(3):66-75.
MA Ya-fei,SUN Wen-kang,HE Yu,et al.Surface crack identification method of concrete bridge based on DC-Unet[J].Journal of Chang'an University(Natural Science Edition),2024,44(3):66-75.
[9]黄凯奇,任伟强,谭铁牛.图像物体分类与检测算法综述[J].计算机学报,2014,378(6):1225-1240.
HUANG Kai-qi,REN Wei-qiang,TAN Tie-niu.A review on image object classification and detection[J].Chinese Journal of Computers,2014,378(6):1225-1240.
[10]PAN B,QIAN K M,XIE H M,et al.Two-dimensional digital image correlation for in-plane displacement and strain measurement:A review[J].Measurement Science and Technology,2009,20(6):062001.
[11]孔颖乔.基于非线性标定的桥梁裂缝精确视频测量技术研究[D].上海:上海交通大学,2017.
KONG Ying-qiao.Research on bridge crack measurement system based on high-precision calibration[D].Shanghai:Shanghai Jiao Tong University,2017.
[12]李亦舜,刘成龙,曹 静,等.基于深度学习的路面病害检测与时空追溯方法[J].长安大学学报(自然科学版),2022,42(6):53-65.
LI Yi-shun,LIU Cheng-long,CAO Jing,et al.Automatic tracking method of pavement performance decay based on deep learning[J].Journal of Chang'an University(Natural Science Edition),2022,42(6):53-65.
[13]RAZA S N,RAZA U R H,LEE S G,et al.Artificial intelligence based camera calibration[C]//IEEE.Proceedings of 2019 15th International Wireless Communications & Mobile Computing Conference.New York:IEEE,2019:1564-1569.
[14]ZHANG Z.A flexible new technique for camera calibration[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(11):1330-1334.
[15]SEO Y,HONG K S.About the self-calibration of a rotating and zooming camera:Theory and practice[C]//IEEE.Proceedings of the Seventh IEEE International Conference on Computer Vision.New York:IEEE,1999:183-189.
[16]FAUGERAS O D,LUONG Q T,MAYBANK S J.Camera self-calibration:Theory and experiments[M]//Spriger.Proceedings of Computer Vision-ECCV'92.Berlin:Springer,1992:321-334.
[17]TRIGGS B.Autocalibration from planar scenes[M].Berlin:Springer,1998.
[18]许薛军,张肖宁.基于数字图像的混凝土桥梁裂缝检测技术[J].湖南大学学报(自然科学版),2013,40(7):34-40.
XU Xue-jun,ZHANG Xiao-ning.Crack detection of concrete bridges based digital image[J].Journal of Hunan University(Natural Science),2013,40(7):34-40.
[19]GOMEZ-OJEDA R,BRIALES J,FERNANDEZ-MORAL E,et al.Extrinsic calibration of a 2D laser-rangefinder and a camera based on scene corners[C]//IEEE.Proceedings of 2015 IEEE International Conference on Robotics and Automation.Seattle.New York:IEEE,2015:3611-3616.
[20]黄志清,苏 毅,王庆文,等.二维激光雷达与可见光相机外参标定方法研究[J].仪器仪表学报,2020,41(9):121-129.
HUANG Zhi-qing,SU Yi,WANG Qing-wen,et al.Research on extrinsic parameter calibration method of 2D laser rangefinder(LRF)and visible light camera[J].Chinese Journal of Scientific Instrument,2020,41(9):121-129.
[21]崔 灿,鲁寨军,黄 磊.线激光辅助单目视觉测量铁路侵限异物尺寸[J].铁道科学与工程学报,2017,14(2):349-354.
CUI Can,LU Zhai-jun,HUANG Lei.A size measurement method for the foreign objects in railway lines using monocular vision and linear laser[J].Journal of Railway Science and Engineering,2017,14(2):349-354.
[22]PAN X J,WU J Y,LI Z L,et al.Self-calibration for linear structured light 3D measurement system based on quantum genetic algorithm and feature matching[J].Optik,2021,225:165749.
[23]金萍萍.图像拼接和裂缝提取方法研究及在多足机器人桥梁检测中的应用[D].广州:华南理工大学,2015.
JIN Ping-ping.Research on image mosaic and crack extraction method and their applications in bridge inspection based on multi-legged robot[D].Guangzhou:South China University of Technology,2015.
[24]程 斌,黄 斌,李得睿.基于平行激光测距的图像自标定方法[J].上海交通大学学报,2022,56(7):850-857.
CHENG Bin,HUANG Bin,LI De-rui.Image self-calibration method based on parallel laser ranging[J].Journal of Shanghai Jiao Tong University,2022,56(7):850-857.
[25]张清华,李 俊,郭亚文,等.正交异性钢桥面板结构体系的疲劳破坏模式和抗力评估[J].土木工程学报,2019,52(1):71-81.
ZHANG Qing-hua,LI Jun,GUO Ya-wen,et al.Fatigue failure modes and resistance evaluation of orthotropic steel bridge deck structural system[J].China Civil Engineering Journal,2019,52(1):71-81.

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Last Update: 2025-02-25