Article(id=1156908296864097123, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156908295593223005, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2308856, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1699632000000, receivedDateStr=2023-11-11, revisedDate=1721577600000, revisedDateStr=2024-07-22, acceptedDate=null, acceptedDateStr=null, onlineDate=1753758032289, onlineDateStr=2025-07-29, pubDate=1736265600000, pubDateStr=2025-01-08, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753758032289, onlineIssueDateStr=2025-07-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753758032289, creator=13701087609, updateTime=1753758032289, updator=13701087609, issue=Issue{id=1156908295593223005, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='1', pageStart='1', pageEnd='438', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753758031985, creator=13701087609, updateTime=1765425680602, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1205845960933049001, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156908295593223005, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1205845960933049002, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156908295593223005, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=383, endPage=393, ext={EN=ArticleExt(id=1156908297359025002, articleId=1156908296864097123, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Monitoring Method of Bridge Structure Displacement Based on Camera Pinhole Model, columnId=1156262728772735295, journalTitle=Science Technology and Engineering, columnName=Papers·Traffics and Transportations, runingTitle=null, highlight=null, articleAbstract=

The displacement response of a bridge is identified as a fundamental condition for the structural health monitoring and safety assessment of bridge structures. In order to fully leverage the advantages of machine vision for measuring structural displacements and to enhance its applicability, a structural displacement monitoring method based on the pinhole camera model was proposed. Sparse optical flow was employed to track structural feature points, achieving sub-pixel level image displacements. By employing the optical geometric relationships of camera imaging, an analytical solution was established between real-world displacements and image displacements. The image displacements were then substituted into algebraic relationships to obtain the true structural displacements. In the indoor experiments on dynamic load displacement identification of a simply supported bridge model, compared to the measurements obtained using a linear variable differential transformer displacement meter, the proposed method achieves a maximum error within 6% for pitch angles up to 30° and yaw angles up to 35°, thereby meeting the application requirements for monitoring the displacement deformations of bridge structures.

, correspAuthors=Zhi-xiang ZHOU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jun-chen LIU, Wei-zhu ZHU, Zhi-xiang ZHOU, Xi CHU, Zi-meng SHEN), CN=ArticleExt(id=1156908436848992782, articleId=1156908296864097123, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于相机针孔模型的桥梁结构位移监测方法, columnId=1156262730664366426, journalTitle=科学技术与工程, columnName=论文·交通运输, runingTitle=null, highlight=null, articleAbstract=

桥梁的位移响应是桥梁结构健康监测和安全状态评估的重要基础条件。为了充分利用机器视觉测量结构位移的优点,并提高其适用性,可以满足拍摄设备带有姿态角的情况下的结构位移拍摄的精度,提出了一种基于相机针孔模型的结构位移监测方法。利用稀疏光流对结构特征点进行追踪,得到亚像素级的图像位移,通过相机成像的光学几何关系,建立了现实世界位移和图像位移之间的解析解,将图像位移代入代数关系,进而得到结构真实位移。在室内开展简支模型桥动载位移识别试验中,与线性可变差动变压器位移计测量结果相比,当俯仰角在30°、偏航角在35°以内时,本文方法位移监测最大误差在6%以内,满足桥梁结构位移变形监测的应用需求。

, correspAuthors=周志祥, authorNote=null, correspAuthorsNote=
* 周志祥(1958—),男,汉族,四川遂宁人,博士,教授,博士研究生导师。研究方向:桥梁健康检测与监测。E-mail:
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刘俊辰(1999—),男,汉族,四川达州人,硕士研究生。研究方向:桥梁健康检测与监测。E-mail:

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刘俊辰(1999—),男,汉族,四川达州人,硕士研究生。研究方向:桥梁健康检测与监测。E-mail:

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刘俊辰(1999—),男,汉族,四川达州人,硕士研究生。研究方向:桥梁健康检测与监测。E-mail:

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displacement surface for scenario 1-1, figureFileSmall=2GYSUEtOJOATa3RvjlC7nw==, figureFileBig=LAB7r+snbw/jolrMZlt8pA==, tableContent=null), ArticleFig(id=1205909223230206529, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=CN, label=图12, caption=工况1-1的时域、空域连续位移曲面, figureFileSmall=2GYSUEtOJOATa3RvjlC7nw==, figureFileBig=LAB7r+snbw/jolrMZlt8pA==, tableContent=null), ArticleFig(id=1205909223297315394, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=EN, label=Fig.13, caption=Displacement time history curves at every locations under scenario 1-1, figureFileSmall=gutQ0Oe/SHco8H+ZC3RXzQ==, figureFileBig=esc5hizoRnQVfQkv2jQ0kw==, tableContent=null), ArticleFig(id=1205909223351841347, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=CN, label=图13, caption=工况1-1下各处位移时程曲线, figureFileSmall=gutQ0Oe/SHco8H+ZC3RXzQ==, figureFileBig=esc5hizoRnQVfQkv2jQ0kw==, tableContent=null), ArticleFig(id=1205909223427338820, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=EN, label=Table 1, caption=

Yaw angle test scenario

, figureFileSmall=null, figureFileBig=null, tableContent=
工况
编号
主光角/
(°)
偏航角/
(°)
工况
编号
主光角/
(°)
偏航角/
(°)
1-1 0 0 3-5 10 20
1-2 0 5 3-6 10 25
1-3 0 10 3-7 10 30
1-4 0 15 3-8 10 35
1-5 0 20 4-1 15 0
1-6 0 25 4-2 15 5
1-7 0 30 4-3 15 10
1-8 0 35 4-4 15 15
2-1 5 0 4-5 15 20
2-2 5 5 4-6 15 25
2-3 5 10 4-7 15 30
2-4 5 15 4-8 15 35
2-5 5 20 5-1 20 0
2-6 5 25 5-2 20 5
2-7 5 30 5-3 20 10
2-8 5 35 5-4 20 15
3-1 10 0 5-5 20 20
3-2 10 5 5-6 20 25
3-3 10 10 5-7 20 30
3-4 10 15 5-8 20 35
), ArticleFig(id=1205909223519613509, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=CN, label=表1, caption=

偏航角试验工况表

, figureFileSmall=null, figureFileBig=null, tableContent=
工况
编号
主光角/
(°)
偏航角/
(°)
工况
编号
主光角/
(°)
偏航角/
(°)
1-1 0 0 3-5 10 20
1-2 0 5 3-6 10 25
1-3 0 10 3-7 10 30
1-4 0 15 3-8 10 35
1-5 0 20 4-1 15 0
1-6 0 25 4-2 15 5
1-7 0 30 4-3 15 10
1-8 0 35 4-4 15 15
2-1 5 0 4-5 15 20
2-2 5 5 4-6 15 25
2-3 5 10 4-7 15 30
2-4 5 15 4-8 15 35
2-5 5 20 5-1 20 0
2-6 5 25 5-2 20 5
2-7 5 30 5-3 20 10
2-8 5 35 5-4 20 15
3-1 10 0 5-5 20 20
3-2 10 5 5-6 20 25
3-3 10 10 5-7 20 30
3-4 10 15 5-8 20 35
), ArticleFig(id=1205909223641248326, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=EN, label=Table 2, caption=

Displacement measurements at mid-span cross-section for each scenario

, figureFileSmall=null, figureFileBig=null, tableContent=
工况
编号
LVDT
最大值/mm
计算
最大值/mm
APVE/% NRMSE/% 工况
编号
LVDT
最大值/mm
计算
最大值/mm
APVE/% NRMSE/%
1-1 7.20 7.15 1.94 0.56 3-5 5.92 5.77 2.53 2.57
1-2 6.40 6.55 2.34 2.15 3-6 6.19 6.49 4.85 2.95
1-3 6.60 6.64 0.61 2.03 3-7 6.88 6.59 4.22 2.71
1-4 6.66 6.65 0.15 2.59 3-8 6.03 5.88 2.49 3.54
1-5 6.65 6.60 0.75 2.68 4-1 5.62 5.79 3.02 2.12
1-6 7.33 7.06 3.68 2.40 4-2 7.19 7.41 3.06 2.40
1-7 6.32 6.26 0.95 2.45 4-3 7.42 7.59 2.29 1.93
1-8 7.40 6.97 5.81 3.26 4-4 6.85 6.95 1.46 2.45
2-1 7.09 7.20 1.55 1.84 4-5 7.56 7.68 1.06 1.74
2-2 7.43 7.64 2.83 1.98 4-6 7.19 7.21 0.28 2.60
2-3 7.60 7.75 1.97 1.72 4-7 7.34 7.16 2.45 3.19
2-4 6.71 6.82 1.64 2.20 4-8 6.85 6.67 2.63 3.81
2-5 7.10 7.13 0.42 2.61 5-1 6.89 7.17 4.06 2.57
2-6 7.11 7.21 1.41 2.65 5-2 6.41 6.70 4.52 2.68
2-7 7.45 7.32 1.74 2.89 5-3 7.18 7.38 2.79 2.68
2-8 7.37 7.16 2.85 3.38 5-4 6.95 7.22 3.88 2.85
3-1 6.89 7.11 3.19 2.08 5-5 6.91 7.07 2.32 2.42
3-2 7.21 7.44 3.19 1.94 5-6 6.66 6.77 1.65 2.77
3-3 7.35 7.12 3.13 2.15 5-7 7.28 7.25 0.41 3.20
3-4 7.27 7.09 2.48 2.39 5-8 7.31 7.65 4.65 4.18
), ArticleFig(id=1205909224828236359, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=CN, label=表2, caption=

各工况下跨中截面位移测量结果

, figureFileSmall=null, figureFileBig=null, tableContent=
工况
编号
LVDT
最大值/mm
计算
最大值/mm
APVE/% NRMSE/% 工况
编号
LVDT
最大值/mm
计算
最大值/mm
APVE/% NRMSE/%
1-1 7.20 7.15 1.94 0.56 3-5 5.92 5.77 2.53 2.57
1-2 6.40 6.55 2.34 2.15 3-6 6.19 6.49 4.85 2.95
1-3 6.60 6.64 0.61 2.03 3-7 6.88 6.59 4.22 2.71
1-4 6.66 6.65 0.15 2.59 3-8 6.03 5.88 2.49 3.54
1-5 6.65 6.60 0.75 2.68 4-1 5.62 5.79 3.02 2.12
1-6 7.33 7.06 3.68 2.40 4-2 7.19 7.41 3.06 2.40
1-7 6.32 6.26 0.95 2.45 4-3 7.42 7.59 2.29 1.93
1-8 7.40 6.97 5.81 3.26 4-4 6.85 6.95 1.46 2.45
2-1 7.09 7.20 1.55 1.84 4-5 7.56 7.68 1.06 1.74
2-2 7.43 7.64 2.83 1.98 4-6 7.19 7.21 0.28 2.60
2-3 7.60 7.75 1.97 1.72 4-7 7.34 7.16 2.45 3.19
2-4 6.71 6.82 1.64 2.20 4-8 6.85 6.67 2.63 3.81
2-5 7.10 7.13 0.42 2.61 5-1 6.89 7.17 4.06 2.57
2-6 7.11 7.21 1.41 2.65 5-2 6.41 6.70 4.52 2.68
2-7 7.45 7.32 1.74 2.89 5-3 7.18 7.38 2.79 2.68
2-8 7.37 7.16 2.85 3.38 5-4 6.95 7.22 3.88 2.85
3-1 6.89 7.11 3.19 2.08 5-5 6.91 7.07 2.32 2.42
3-2 7.21 7.44 3.19 1.94 5-6 6.66 6.77 1.65 2.77
3-3 7.35 7.12 3.13 2.15 5-7 7.28 7.25 0.41 3.20
3-4 7.27 7.09 2.48 2.39 5-8 7.31 7.65 4.65 4.18
), ArticleFig(id=1205909224899539528, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=EN, label=Table 3, caption=

Displacement measurements at mid-span cross-section for each scenario

, figureFileSmall=null, figureFileBig=null, tableContent=
工况
编号
俯仰
角/(°)
LVDT最
大值/mm
计算最
大值/mm
APVE/% NRMSE/%
1-1 0 5.49 5.66 3.10 2.17
1-2 5 5.88 6.00 2.04 2.49
1-3 10 5.91 5.96 0.85 2.72
1-4 15 6.01 6.06 0.83 2.06
1-5 20 6.04 6.01 0.50 2.35
1-6 25 6.39 6.46 1.10 2.40
1-7 30 5.98 6.13 2.51 3.03
), ArticleFig(id=1205909224991814217, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=CN, label=表3, caption=

各工况下跨中截面位移测量结果

, figureFileSmall=null, figureFileBig=null, tableContent=
工况
编号
俯仰
角/(°)
LVDT最
大值/mm
计算最
大值/mm
APVE/% NRMSE/%
1-1 0 5.49 5.66 3.10 2.17
1-2 5 5.88 6.00 2.04 2.49
1-3 10 5.91 5.96 0.85 2.72
1-4 15 6.01 6.06 0.83 2.06
1-5 20 6.04 6.01 0.50 2.35
1-6 25 6.39 6.46 1.10 2.40
1-7 30 5.98 6.13 2.51 3.03
), ArticleFig(id=1205909225063117386, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=EN, label=Table 4, caption=

Test scenario

, figureFileSmall=null, figureFileBig=null, tableContent=
工况编号 俯仰角/(°) 偏航角/(°) 测量距离/m
1-1 0 0 4.8
1-2 0 8 4.8
1-3 0 16 4.8
1-4 0 24 4.8
1-5 0 32 4.8
2-1 5 0 4.8
2-2 5 8 4.8
2-3 5 16 4.8
2-4 5 24 4.8
2-5 5 32 4.8
3-1 10 0 4.8
3-2 10 8 4.8
3-3 10 16 4.8
3-4 10 24 4.8
3-5 10 32 4.8
), ArticleFig(id=1205909225147003467, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=CN, label=表4, caption=

试验工况表

, figureFileSmall=null, figureFileBig=null, tableContent=
工况编号 俯仰角/(°) 偏航角/(°) 测量距离/m
1-1 0 0 4.8
1-2 0 8 4.8
1-3 0 16 4.8
1-4 0 24 4.8
1-5 0 32 4.8
2-1 5 0 4.8
2-2 5 8 4.8
2-3 5 16 4.8
2-4 5 24 4.8
2-5 5 32 4.8
3-1 10 0 4.8
3-2 10 8 4.8
3-3 10 16 4.8
3-4 10 24 4.8
3-5 10 32 4.8
), ArticleFig(id=1205909225230889548, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=EN, label=Table 5, caption=

Displacement measurements at cross-section for each scenario

, figureFileSmall=null, figureFileBig=null, tableContent=
工况
编号
监测
位置
LVDT最
大值/mm
计算最
大值/mm
APVE/% NRMSE/%
L/4 3.48 3.39 2.30 4.31
1-1 L/2 4.71 4.80 1.91 4.90
3L/4 3.01 2.88 4.30 5.12
L/4 3.38 3.40 0.59 4.65
1-2 L/2 4.50 4.57 1.58 4.80
3L/4 2.84 2.74 3.76 3.45
L/4 3.84 3.72 3.09 4.46
1-3 L/2 5.21 5.10 2.00 4.36
3L/4 3.18 3.10 2.62 3.69
L/4 3.93 3.79 3.56 3.82
1-4 L/2 5.29 5.06 4.35 4.49
3L/4 2.87 3.02 4.99 3.51
L/4 3.97 3.84 3.44 4.48
1-5 L/2 5.44 5.43 3.68 3.44
3L/4 3.31 3.29 3.95 4.70
L/4 4.66 4.45 4.51 4.61
2-1 L/2 3.63 3.83 5.19 3.47
3L/4 6.25 6.24 1.12 4.56
L/4 4.08 3.96 2.88 4.12
2-2 L/2 5.55 5.48 1.26 3.71
3L/4 3.54 3.37 4.80 2.50
L/4 4.88 4.62 5.33 5.07
2-3 L/2 6.74 6.48 4.11 5.05
3L/4 4.03 3.92 2.94 4.08
L/4 4.40 4.35 1.01 2.09
2-4 L/2 6.40 6.15 3.95 3.91
3L/4 4.03 3.84 4.87 5.13
L/4 3.84 3.66 4.69 3.96
2-5 L/2 5.21 5.06 2.88 4.32
3L/4 3.11 3.06 1.61 3.27
L/4 4.23 4.11 2.84 5.13
3-1 L/2 5.78 5.52 4.50 3.18
3L/4 3.44 3.54 2.91 4.29
L/4 3.91 3.81 2.56 5.18
3-2 L/2 5.13 5.29 3.12 5.27
3L/4 3.11 3.22 3.54 3.89
L/4 3.82 3.97 3.93 2.63
3-3 L/2 5.26 5.47 3.99 2.65
3L/4 3.44 3.31 3.78 3.50
L/4 3.84 3.75 2.34 5.15
3-4 L/2 5.05 5.12 1.39 5.11
3L/4 3.14 3.07 2.23 4.78
L/4 3.74 3.60 3.89 4.97
3-5 L/2 5.15 5.01 2.72 4.41
3L/4 3.12 2.97 4.81 4.72
), ArticleFig(id=1205909225306387021, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908296864097123, language=CN, label=表5, caption=

各工况下截面位移测量结果

, figureFileSmall=null, figureFileBig=null, tableContent=
工况
编号
监测
位置
LVDT最
大值/mm
计算最
大值/mm
APVE/% NRMSE/%
L/4 3.48 3.39 2.30 4.31
1-1 L/2 4.71 4.80 1.91 4.90
3L/4 3.01 2.88 4.30 5.12
L/4 3.38 3.40 0.59 4.65
1-2 L/2 4.50 4.57 1.58 4.80
3L/4 2.84 2.74 3.76 3.45
L/4 3.84 3.72 3.09 4.46
1-3 L/2 5.21 5.10 2.00 4.36
3L/4 3.18 3.10 2.62 3.69
L/4 3.93 3.79 3.56 3.82
1-4 L/2 5.29 5.06 4.35 4.49
3L/4 2.87 3.02 4.99 3.51
L/4 3.97 3.84 3.44 4.48
1-5 L/2 5.44 5.43 3.68 3.44
3L/4 3.31 3.29 3.95 4.70
L/4 4.66 4.45 4.51 4.61
2-1 L/2 3.63 3.83 5.19 3.47
3L/4 6.25 6.24 1.12 4.56
L/4 4.08 3.96 2.88 4.12
2-2 L/2 5.55 5.48 1.26 3.71
3L/4 3.54 3.37 4.80 2.50
L/4 4.88 4.62 5.33 5.07
2-3 L/2 6.74 6.48 4.11 5.05
3L/4 4.03 3.92 2.94 4.08
L/4 4.40 4.35 1.01 2.09
2-4 L/2 6.40 6.15 3.95 3.91
3L/4 4.03 3.84 4.87 5.13
L/4 3.84 3.66 4.69 3.96
2-5 L/2 5.21 5.06 2.88 4.32
3L/4 3.11 3.06 1.61 3.27
L/4 4.23 4.11 2.84 5.13
3-1 L/2 5.78 5.52 4.50 3.18
3L/4 3.44 3.54 2.91 4.29
L/4 3.91 3.81 2.56 5.18
3-2 L/2 5.13 5.29 3.12 5.27
3L/4 3.11 3.22 3.54 3.89
L/4 3.82 3.97 3.93 2.63
3-3 L/2 5.26 5.47 3.99 2.65
3L/4 3.44 3.31 3.78 3.50
L/4 3.84 3.75 2.34 5.15
3-4 L/2 5.05 5.12 1.39 5.11
3L/4 3.14 3.07 2.23 4.78
L/4 3.74 3.60 3.89 4.97
3-5 L/2 5.15 5.01 2.72 4.41
3L/4 3.12 2.97 4.81 4.72
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基于相机针孔模型的桥梁结构位移监测方法
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刘俊辰 1 , 朱伟铸 2 , 周志祥 2, * , 楚玺 2 , 沈梓蒙 1
科学技术与工程 | 论文·交通运输 2025,25(1): 383-393
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科学技术与工程 | 论文·交通运输 2025, 25(1): 383-393
基于相机针孔模型的桥梁结构位移监测方法
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刘俊辰1 , 朱伟铸2, 周志祥2, * , 楚玺2, 沈梓蒙1
作者信息
  • 1.重庆交通大学土木工程学院, 重庆 400074
  • 2.深圳大学土木与交通工程学院, 深圳 518061
  • 刘俊辰(1999—),男,汉族,四川达州人,硕士研究生。研究方向:桥梁健康检测与监测。E-mail:

通讯作者:

* 周志祥(1958—),男,汉族,四川遂宁人,博士,教授,博士研究生导师。研究方向:桥梁健康检测与监测。E-mail:
Monitoring Method of Bridge Structure Displacement Based on Camera Pinhole Model
Jun-chen LIU1 , Wei-zhu ZHU2, Zhi-xiang ZHOU2, * , Xi CHU2, Zi-meng SHEN1
Affiliations
  • 1. School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
  • 2. College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518061, China
出版时间: 2025-01-08 doi: 10.12404/j.issn.1671-1815.2308856
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桥梁的位移响应是桥梁结构健康监测和安全状态评估的重要基础条件。为了充分利用机器视觉测量结构位移的优点,并提高其适用性,可以满足拍摄设备带有姿态角的情况下的结构位移拍摄的精度,提出了一种基于相机针孔模型的结构位移监测方法。利用稀疏光流对结构特征点进行追踪,得到亚像素级的图像位移,通过相机成像的光学几何关系,建立了现实世界位移和图像位移之间的解析解,将图像位移代入代数关系,进而得到结构真实位移。在室内开展简支模型桥动载位移识别试验中,与线性可变差动变压器位移计测量结果相比,当俯仰角在30°、偏航角在35°以内时,本文方法位移监测最大误差在6%以内,满足桥梁结构位移变形监测的应用需求。

桥梁工程  /  计算机视觉  /  位移监测  /  针孔模型  /  倾斜摄影

The displacement response of a bridge is identified as a fundamental condition for the structural health monitoring and safety assessment of bridge structures. In order to fully leverage the advantages of machine vision for measuring structural displacements and to enhance its applicability, a structural displacement monitoring method based on the pinhole camera model was proposed. Sparse optical flow was employed to track structural feature points, achieving sub-pixel level image displacements. By employing the optical geometric relationships of camera imaging, an analytical solution was established between real-world displacements and image displacements. The image displacements were then substituted into algebraic relationships to obtain the true structural displacements. In the indoor experiments on dynamic load displacement identification of a simply supported bridge model, compared to the measurements obtained using a linear variable differential transformer displacement meter, the proposed method achieves a maximum error within 6% for pitch angles up to 30° and yaw angles up to 35°, thereby meeting the application requirements for monitoring the displacement deformations of bridge structures.

bridge engineering  /  computer vision  /  displacement monitoring  /  pinhole model  /  tilted photography
刘俊辰, 朱伟铸, 周志祥, 楚玺, 沈梓蒙. 基于相机针孔模型的桥梁结构位移监测方法. 科学技术与工程, 2025 , 25 (1) : 383 -393 . DOI: 10.12404/j.issn.1671-1815.2308856
Jun-chen LIU, Wei-zhu ZHU, Zhi-xiang ZHOU, Xi CHU, Zi-meng SHEN. Monitoring Method of Bridge Structure Displacement Based on Camera Pinhole Model[J]. Science Technology and Engineering, 2025 , 25 (1) : 383 -393 . DOI: 10.12404/j.issn.1671-1815.2308856
桥梁在运营的期间,势必会经受车辆荷载、结构自重和地震等动静荷载的影响,而桥梁结构在受到荷载作用的情况下会产生位移响应,通过监测结构的位移便可以得知桥梁刚度信息,而局部的位移异常可能表示结构的刚度损伤[1-3]
目前常用的位移测量方法包括接触式和非接触式2类。其中接触式位移测量方法通常采用百分表、线性可变差压传感器(linear variable differential transformer,LVDT)等。这类测量方法因为其原理,需要通过传感器与被测结构的测点接触,通过结构的位移带动传感器测量部位产生量变位移进而得到实际测点位移,一般来说精度较高,但是需要在结构处为其搭建平台放置传感器,对于大跨等净空较高的桥梁,可操作性较低,操作较为烦琐。非接触式位移测量方法通常包括全球定位系统(global positioning system,GPS)、激光多普勒仪、全站仪、雷达干涉系统和计算机视觉位移测量等。其中GPS因其相对较低的测量精度和采样频率主要应用于大跨度的桥梁和高耸结构,无法实时测量位移变形[4-5];激光多普勒仪的使用成本较高,且只能单点测量[6];全站仪需要在结构上安装反光原件,并且采样频率较低,难以实现结构位移的动态实时测量[7-9]。雷达干涉同样需要提前安装反光原件,操作较为复杂[10-11]
而属于非接触式测量方法的基于计算机视觉测量方法,由于其具有远距离、非接触、高精度、全场性、操作简便等众多优点,得到了广泛的应用研究。该方法主要原理是利用对相机拍摄的被测结构视频进行目标追踪算法处理,得到被测点在相机图像中的运动轨迹,再通过图像与现实世界的几何映射关系确定结构的真实位移变形数据[3]。已有大量实际工程案例证明基于计算机视觉的位移测量方法是切实可行的。例如,Chen等[12]讨论了使用基于相机的振动测量方法测量桥梁的位移响应,并使用基于相机的测量进行系统识别。Ngeljaratan等[13]利用目标跟踪数字图像相关(digital image correlation,DIC)技术,监测在双向地震震动下测试的桥梁结构的响应。
但是面对量大面广的常规跨径桥梁,现有计算机视觉位移监测研究中存在一定的局限性。首先是这些研究的实验设置需要让光轴尽量垂直于感兴趣的结构平面,一般而言,相机和桥梁纵向的夹角越接近90 °,图像受镜头畸变的影响越小,像素比例因子越稳定,测量结果会越精确,而倾角越大,误差则会随之急剧增大[14-16]。要实现这一点就需要在检测目标之外选取一个理想的摄像机拍摄点。在大量桥梁的监测应用中,为桥梁寻找这样一个监测的不动点是困难的,有相当大的局限性[18]
目前,针对光轴垂直于结构面的位移测量方法已经比较成熟,并且精度达到了比较理想的结果,对于倾斜情况下的测量方法则处于深入研究阶段。Tian等[17-18]在无畸变针孔成像模型的基础上,提出了一种离轴DIC视频偏转仪的广义SF标定模型,并在室内悬臂梁试验验证了该方法的准确性,高速铁路桥现场试验验证了该方法的鲁棒性和实用性。但是,对于相机姿态的偏航角和俯仰角相结合的位移监测方法还研究较少。
因此,在以上的基础下,结合课题组已有研究成果[19-22],现提出一种基于针孔模型的桥梁结构高精度位移监测方法。在实验室搭建的一座工字钢梁焊接简支梁桥模型上,开展不同距离、不同俯仰角、偏航角和主光角(chief ray angle)工况下的动荷载试验,利用一台Sony高清民用摄像机作为影像数据采集设备,LVDT位移传感器同时采集位移数据,通过不同工况下的影像计算位移于位移计采集实时位移进行对比,分别以单点单一角度变量和多点多角度试验以验证所提出位移计算方法的有效性。
所提出的倾斜姿态下的针孔模型位移监测方法主要由以下几个步骤方面组成:针对目标点的稀疏光流特征点追踪、建立图像位移与现实位移映射关系。
由于目标对象或者摄像机的移动造成的图像对象在连续两帧图像中的移动被称为光流。光流对应用场景提出了3个假设先验:亮度是恒定的,即图像中对象的像素亮度在连续帧之间不会改变;短距离运动,相邻帧之间的时间足够短,并且物体的运动很小;空间一致性,相邻像素具有相似的运动。
在给定t时刻的图像上的像素点I(x,y),在tt时刻运动到(xx,yy)处,则有
I(x,y,t)=I(xx,yy,tt)
式(1)利用泰勒展开,保留一阶,则有
I(x,y,t)= I xδx+ I yδy+ I tδt
式中:∂I/∂x和∂I/∂y为当前时刻图像在xy方向的梯度;∂I/∂t为图像灰度对时间的变化量,也就是下一帧与当前帧的差分,δx和δy即为求解的像素运动。因为下一时刻的灰度等于之前的灰度,由此可得
I xδx+ I yδy+ I tδt=0
同时除以,δt移项得
I x δ x δ t+ I y δ y δ t=- I t
u= δ x δ t,v= δ y δ t,Ix= I x,Iy= I y,It= I t
式(5)中:uv分别为像素在x轴和y轴上的运动速度,写成矩阵形式为
[ I x I y] u v=-It
此时方程个数大于未知数个数,可以通过周围像素求解中心像素运动建立方程组为
[ I x I y ] k u v=-Itk, k=1,2,…,w2
A= [ I x I y ] 1 [ I x I y ] 2 [ I x I y ] k, b= I t 1 I t 2 I t k
A u v=-b
通过方程组可以得到像素运动速度,进而求得像素位移。由于采用了最小二乘法估计和梯度运算,特征点上的光流实现了亚像素估计,追踪区域内所有特征点的位移平均值保留了亚像素特征,因而可以达到亚像素级位移监测[23]
通过稀疏光流追踪可以得到监测点在图像上的每一帧的图像坐标系上像素坐标,但是从图像坐标得到现实世界的实际位移,需要进行系列运算,找到其映射关系。
当相机处于正视的条件下,光轴与结构面和感光元件垂直,光心O到结构面的垂直距离为D,结构面与结构图像在光轴上距离D上的投影图像重合。利用在相机姿态存在角度的条件下的位移监测方法,因此,在相机绕光心O只发生偏航角上的转动时,则相对偏航角ψ为转动前后光轴的夹角。转动后,投影面与结构面关系如图1所示,在转动后的成像平面与光心O对称是为虚拟成像平面。
如果相机是逆时针转动时,则成像范围内的结构面虚像上的点存在3种情况,即面上的点处在成像平面左侧、中点和右侧,分开讨论3种情况。
当点处于左侧,即FE<FD时,有
( x F - x E ) 2 - ( y F - y E ) 2< ( x F - x D ) 2 - ( y F - y D ) 2
式(10)中:xFyF为成像范围虚像边缘点F的像素坐标;xEyE为结构面虚像上一点E的像素坐标;xDyD为成像平面虚像中心点D的像素坐标。
OD为光心O到感光元件上中心点D对应的实际位置的物理距离;DE为光感光元件上中心点D和结构点E对应的实际位置的物理距离。此时光心到感光元件上结构点E对应的实际位置的物理距离OE
OE= f 2 + [ ( x E - x D ) 2 + ( y E - y D ) 2 ] S 2
式(11)中:S为感光元件的像元尺寸,即感光元件上每个像元的实际物理尺寸;f为相机焦距。根据几何关系可得
O E s i n ( π / 2 )= f s i n β
移项化简得
$\beta=\arcsin \left(\frac{f}{O E}\right)$
根据角度对应关系,易知β=α+γα=φ+ψ,则可以推出
EOM=φ+γ=β-α+α-ψ=β-ψ
式(14)中:βOE与成像平面虚像相交所成的夹角;αOF与成像平面虚像相交所成的夹角;γOFOE所成的夹角;φ为结构面与OH所成的夹角;OI为光心O到结构点的距离。则有
OI= D s i n E O M
代入已知条件
OI= D s i n s i n - 1 f f 2 + S 2 [ ( x E - x D ) 2 + ( y E - y D ) 2 ] - ψ
当点与交点重合,即FE=FD时,有α+γ/2,α=φ+ψ,则
EOM=φ+γ/2-ψ
OI= D s i n E O M= D s i n ( π / 2 - ψ )= D c o s ψ
当处于右侧,即FE>FD时,有
( x F - x E ) 2 - ( y F - y E ) 2> ( x F - x D ) 2 - ( y F - y D ) 2
根据几何关系可得
O E s i n ( π / 2 )= f s i n β
移项化简得
$\beta=\arcsin \left(\frac{f}{O E}\right)$
根据角度对应关系,易知α+γ=π-βα=φ+ψ,则可以推出
EOM=φ+γ=π-β-ψ
sin∠EOM=sin(β+ψ)
代入已知条件
OI= D s i n s i n - 1 f f 2 + [ ( x E - x D ) 2 + ( y E - y D ) 2 ] S 2 + ψ
当相机光轴垂直于结构面时,如果相机绕光心O只发生俯仰角上的转动时,则相对俯仰角θ为动前后光轴的夹角。转动后,投影面与结构面关如图2所示,在转动后的成像平面于光心O对称虚拟成像平面。在虚拟成像平面上有
O D 2 + D E 0 2 = E 0 O 2 O D 2 + D E i 2 = E i O 2
式(25)中:E0Ei分别为位移前后的结构点在虚拟成像平面的投影点;OD为焦距f光轴垂直于成像平面;DE0为光感光元件上中心点D和初始点E0对应的实际位置的物理距离;DEi为光感光元件上中心点D和位移后点Ei对应的实际位置的物理距离,则有
D E 0 = S 2 [ ( x D - x E 0 ) 2 + ( y D - y E 0 ) 2 ] D E i = S 2 [ ( x D - x E i ) 2 + ( y D - y E i ) 2 ] E 0 E i = S 2 [ ( x E 0 - x E i ) 2 + ( y E 0 - y E i ) 2 ]
式(26)中:E0Ei为光感光元件上位移前点E0和位移后点Ei对应的实际位置的物理距离; x E 0 y E 0 x E i y E i分别为位移前后的结构点在虚拟成像平面的投影点的像素坐标,代入式(25)中得
E 0 O = f 2 + S 2 ( x D - x E 0 ) 2 + S 2 ( y D - y E 0 ) 2 E i O = f 2 + S 2 ( x D - x E i ) 2 + S 2 ( y D - y E i ) 2
根据余弦定理有
c o s ε = E 0 E i 2 + E 0 O 2 - E i O 2 2 E 0 E i E 0 O c o s δ = E 0 O 2 + E i O 2 - E 0 E i 2 2 E i O E 0 O
由角度对应关系,易知ε=ρ+θρ=ε-θ,则可以推出
ω=π-ρ-δ=π-ε+θ-δ
另外,由正弦定理得
O I 0 s i n ω = I 0 I i s i n δ I 0 I i = O I 0 s i n δ s i n ( δ + ε - θ )
式中:I0Ii为结构监测点的位移大小;OI0为光心到结构初始点距离,OIOI0相同,在1.2.1节已推导。
当相机姿态俯仰角与偏航角并存的情况下时,如图3所示,此时,由于已经存在俯仰角θ,因此,在1.2.1节推论的基础上,可知OIOI0之比为cosθ,则有
OI0= O I c o s θ
代入式(30),可得结构监测点的位移为
I0Ii= O I s i n δ c o s θ s i n ( δ + ε - θ )
式 (32)中:OI为1.2.1节推导的3种情况下的值,代入后分别得到在3种情况下的位移。
在实验室焊接工字钢梁桥模型上开展了荷载试验以研究所提出位移监测方法的适用性。该模型桥为新型装配式钢混组合梁桥的模型桥,桥型为简支梁桥,试件尺寸和构造如图4所示。主梁部分由两片预制铝合金工字钢组成,工字钢总高100 mm,宽50 mm,翼缘厚5 mm,腹板厚5 mm,两片平行工字钢由三个空心矩形钢焊接固定成整体,矩形钢材料和主梁相同,分布在桥梁长度方向的两端和跨中。桥道板采用有机玻璃,截面为矩形,高10 mm,宽500 mm,采用亚克力胶水将桥道板与主梁黏接在一起。模型桥两端放置于铰支座,计算跨径5.64 m。
在模型桥1/4、1/2、3/4跨位置分别布置1个标靶点,1个LVDT位移传感器。传感器采样频率均设置为25 Hz,配合江苏东华测试公司的动态采集仪DH5902N进行位移采集。影像采集采用索尼FDR AX-704K摄像机,帧率设置为25 FPS,传感器为一英寸CMOS,像素分辨率是3 840 pixel×2 160 pixel。
试验分为两个部分,首先进行模型在单一角度变量下单一标靶点精度验证和适用范围,然后针对不同偏航角和俯仰角并存的情况的多标靶工况下,验证方法在实际工程中的应用情景与可行性。每一个工况试验过程中用三脚架将摄像机固定,利用三轴陀螺仪确定相机倾斜角,保持摄像机与模型桥结构面垂直距离不变。采用蓝牙遥控器控制拍摄,并且在试验开始前,采用张氏标定法,进行了设备的畸变矫正,减少震动误差和畸变误差带来的影响。加载小车重量为25 kg,采用连接变频器的电动机匀速牵引小车通过模型桥,在数据清零后同时采集位移计与视频数据,试验数据采集现场照片如图5所示。
为了保证提出的方法精度能够满足实际工程需求,针对俯仰角和偏航角,分别进行了单一角度变量的验证试验,与LVDT位移数据进行误差比较。
偏航角精度验证试验一共设计进行5个大工况下的一共40组小工况,变量涉及主光角和偏航角的变化,主光角(chief ray angle, CRA)表示镜头主光线与光轴的夹角。如图6所示,主光线是从被观测物体发射,经孔径光阑的中心到成像的光线。其中,a号光线主光角超过传感器CRA,光线无法到达光电转换区域;b号c号主光角小于传感器CRA,光线可以到达光电转换区域。
对跨中位置标靶进行位移追踪计算,具体工况如表1所示,光心到结构面垂直距离D为1.56 m,保持不变,如图7所示,通过平移摄像机改变偏航角和主光角大小。
以工况1-1为例,图8为工况1-1下LVDT实测位移与计算位移的对比结果。可以看出,工况下实测位移与针孔模型计算位移结果几乎一致。采用Savitzky-Golay平滑滤波算法对位移时程曲线进行多项式拟合,进行数据的平滑滤波。在克服了曲线数据波动的同时保留主梁位移的变化趋势。可以更加清晰直观地看出两种结果的误差大小,进而方便误差定量分析。
定量分析针孔模型计算位移的误差和精度,对比方法采用以LVDT测得位移为参考,利用归一化均方根误差(normalized root mean square error,NRMSE)和绝对峰值误差(absolute peak value error,APVE)来评估计算方法的误差,其计算公式分别为
NRMSE= 1 n i = 1 n ( x i - y i ) 2 m a x ( y i ) - m i n ( y i )×100%
APVE= m a x x i - m i n y i m a x y i×100%
式中:n为测量数据的总数;xiyi分别为计算位移值和LVDT得到的第i个位移。两种方式测量的跨中截面最大位移和计算得到的两种误差结果如表2所示。
在上述偏航角精度验证所有工况中,提出的针孔模型方法计算位移与LVDT的NRMSE误差最大为4.18%,APVE误差最大为5.81%。两种方式测量的位移曲线虽存在差异,但是NRMSE在5%以内,APVE误差在6%以内,表明针孔模型位移计算方法精度在该系列工况下,能够满足工程实用需求。
图9为采集示意图,俯仰角精度验证试验一共设计进行8组工况,因为结构点位移方向是处于俯仰角同一平面,故变量不涉及主光角的变化。光心到结构面垂直距离0.67 m,保持不变,通过升降摄像机高度改变俯仰角大小。
同样以工况1-1为例,图10为工况1-1下LVDT实测位移与针孔模型方法计算位移的对比,位移时程曲线基本拟合。
以LVDT测得位移为参考,利用归一化均方根误差和绝对峰值误差来评估计算方法的误差。各工况误差计算结果如表3所示。
在上述工况中,提出的针孔模型方法计算位移与LVDT的NRMSE误差最大为3.03%,APVE误差最大为3.1%,误差均在4%以内,表明针孔模型位计算方法精度在该系列工况下,满足桥梁结构变形监测的应用需求。
通过精度验证试验证明本文方法满足在偏航角0°~35°和俯仰角在0°~30°的范围内的精度需求,因而在全桥范围条件下,设置更符合实际工程应用的工况进行实验,所采用的加载方法和精度评价标准与前文一致,全跨布置3个位移传感器和监测标靶,光轴始终对准跨中标靶点,拍摄示意如图11所示,通过平移摄像机水平位置和调节支架高度改变偏航角和俯仰角大小。
在摄像机不同俯仰角和偏航角下共设计了15个工况的动载试验,具体工况说明如表4所示。
通过对实验中摄像机采集视频中的每一帧图像进行如上处理,即以第1帧图像的作为主梁无荷载情况下的原始标靶位置,将视频中剩余的每帧主梁上标靶位置与原始位置进行叠差,得到像素位移,再将像素位移带入公式进行计算,即可得到在时域和空域上连续的位移曲面。以工况1-1为例,图12为工况1-1下LVDT实测位移与针孔模型方法计算位移对比的时域、空域连续位移曲面图。
图12中,y轴表示主梁纵向上某一点的位置,z轴表示位移,x轴表示时间,取L/4、L/2和3L/4处(L=5.64 m)位移时程曲线与位移计数据作对比,如图13所示。
图13可知,本文方法得到的挠度时程曲线与位移传感器采集到的时程数据有着很好的吻合度:曲线走势、振动幅度、波峰波谷位置基本一致。
余下工况采用相同步骤处理,以LVDT测得位移为参考,利用归一化均方根误差和绝对峰值误差来评估计算方法的误差。各工况误差计算结果如表5所示。
表5可知,本文方法在计算以上工况时的计算位移LVDT的NRMSE误差最大为5.27%,APVE误差最大为5.33%,总体误差控制在6%以内,表明基于针孔模型的位移计算方法精度在该系列工况下,满足桥梁结构变形监测的应用需求。
提出了基于针孔模型的桥梁位移计算方法,完成了15种工况下跨径为5.64 m的简支梁模型桥动载位移识别试验,结论如下。
(1)针对需要在设备倾斜姿态条件下,对桥梁位移进行视频数据采集,提出了基于相机针孔模型的结构位移计算方法。通过相机成像的光学几何关系,推导了三维世界位移和图像像素位移之间的解析解。形成了针对设备倾斜姿态下对桥梁结构位移识别的监测方法。
(2)发现了利用稀疏光流算法可以对目标特征点进行跟踪,与本文方法可以实现结合,获得了亚像素级的像素位移和实际位移。验证了模型在单一角度变量下的精度表现,偏航角在35°以内,NRMSE误差和APVE误差最大分别为4.18%和5.81%,俯仰角在30°以内,误差最大分别为3.03%和3.1%。发现了总体误差趋势:随着设备偏航角和俯仰角度增大时,模型计算误差随之增大,在偏航角不超过35°,俯仰角不超过30°时,具有良好的准确度。
(3)在工字钢简支梁桥模型的多标靶试验,以LVDT的位移测量结果为参考基准,验证了在偏航角和俯仰角都存在的工况下针孔模型位移计算方法的精度,测量结果表明,其NRMSE误差和APVE误差最大分别为5.27%和5.33%,均未超过6%。
(4)研究表明,所提出的基于相机针孔模型的结构位移计算方法具有一定的可行性,在面对需要对结构倾斜拍摄的情况下,具有良好的精度表现、普适性和推广价值,但是目前缺少针对实桥的应用,应针对一座常规跨径梁桥进行长期位移监测,以验证该方法在实际工程应用中的可行性。
  • 国家自然科学基金(51778094)
  • 深圳市自然科学基金重点项目(JCYJ20220818095608018)
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doi: 10.12404/j.issn.1671-1815.2308856
  • 接收时间:2023-11-11
  • 首发时间:2025-07-29
  • 出版时间:2025-01-08
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  • 收稿日期:2023-11-11
  • 修回日期:2024-07-22
基金
国家自然科学基金(51778094)
深圳市自然科学基金重点项目(JCYJ20220818095608018)
作者信息
    1.重庆交通大学土木工程学院, 重庆 400074
    2.深圳大学土木与交通工程学院, 深圳 518061

通讯作者:

* 周志祥(1958—),男,汉族,四川遂宁人,博士,教授,博士研究生导师。研究方向:桥梁健康检测与监测。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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