CN109580137A - A kind of bridge structure displacement influence line measurement method based on computer vision technique - Google Patents

A kind of bridge structure displacement influence line measurement method based on computer vision technique Download PDF

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CN109580137A
CN109580137A CN201811443250.7A CN201811443250A CN109580137A CN 109580137 A CN109580137 A CN 109580137A CN 201811443250 A CN201811443250 A CN 201811443250A CN 109580137 A CN109580137 A CN 109580137A
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displacement
video
computer vision
influence line
bridge
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CN109580137B (en
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徐燕
郑宝锋
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Southeast University
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Southeast University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
    • G01M5/0008—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings of bridges
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G01B11/03—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness by measuring coordinates of points
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
    • G01M5/0041—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by determining deflection or stress

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Image Analysis (AREA)

Abstract

本发明属于结构健康监测技术领域，具体提供了一种基于计算机视觉技术的桥梁结构位移影响线实测方法，先在合适的位置架设相机采集视频，确保结构中待测点均位于相机视野范围内；然后基于计算机视觉原理，从采集的视频中提取结构位移时程d；给定通行车辆的车轴分布和轴重，从采集的视频中提取移动荷载信息A；最后根据移动荷载矩阵A和结构测点位移时程d的关系求解出结构位移影响线IL；本发明在户外试验中操作简单、成本低，不影响桥梁正常运营，可同时提供沿跨长方向多测点的位移影响线信息，方便用于结构损伤定位和损伤程度的量化。

The invention belongs to the technical field of structural health monitoring, and specifically provides a method for measuring the displacement influence line of a bridge structure based on a computer vision technology. A camera is first erected at a suitable position to collect video, so as to ensure that the points to be measured in the structure are all located within the field of view of the camera; Then, based on the principle of computer vision, the structural displacement time history d is extracted from the collected video; given the axle distribution and axle load of the passing vehicle, the moving load information A is extracted from the collected video; finally, according to the moving load matrix A and the structural measuring points The relationship between the displacement time history d is used to solve the structural displacement influence line IL; the invention has simple operation and low cost in the outdoor test, does not affect the normal operation of the bridge, and can simultaneously provide the displacement influence line information of multiple measuring points along the span length direction, which is convenient to use. for structural damage localization and quantification of damage extent.

Description

A kind of bridge structure displacement influence line measurement method based on computer vision technique
Technical field
The invention belongs to structural health monitoring technology fields, provide a kind of bridge structure based on computer vision technique Displacement influence line measurement method.
Background technique
The displacement influence line of bridge structure corresponding observation point change in displacement song when referring to traveling load by entire span Line can reflect structure information of overall importance.Common application is bridge structural damage identification, using damage front and back displacement influence line and The positioning and degree quantization of structural damage are realized in the variation of its relevant parameter.
Line measurement method is influenced, common are two kinds, pointwise test obtains Bridge Influence Line by way of static test, Quasi-static influence line is obtained by way of demarcating vehicle and at the uniform velocity passing a bridge.Traditional influence line measured test, due to sensor bridge Upper installation and the control of vehicle loading position, often will affect the daily operation of bridge structure, and experimentation cost is high, working efficiency It is low.It is therefore proposed that a kind of economical and practical Bridge Influence Line measurement method, tool have very important significance.
Summary of the invention
To solve the above problems, the invention discloses a kind of bridge structure displacement influence line based on computer vision technique Measurement method, it is easy to operate, at low cost in test outdoors, bridge normal operation is not influenced, can be provided simultaneously along span length direction The displacement influence line information of multi-measuring point, is conveniently used for the quantization of construction damage positioning and degree of injury.
In order to achieve the above objectives, technical scheme is as follows:
A kind of bridge structure displacement influence line measurement method based on computer vision technique, comprising the following steps:
S1: camera is set up in place and acquires video, it is ensured that tested point is respectively positioned within the scope of camera fields of view in structure；
S2: being based on principle of computer vision, and displacement structure time-histories d is extracted from the video of acquisition；
S21: one or more monitoring objective is selected in video initial frame, is located at m in picture plane1；
S22: according to the projection imaging relationship at four or more control point with monitoring objective in the same plane, meter Plane homography H is calculated, wherein α m=HZ, α is the ratio of any scale, and m is that two dimension of the control point in picture plane is sat Mark, Z are the actual physics coordinate at control point；
S23: being based on Lucas-Kanade optical flow algorithm, positions position m of the object in next video framek；It is specific real Existing process is to be based on Shi-Tomasi Corner Detection, identify the key feature points (x, y) in target area；Based on brightness perseverance It is fixed it is assumed that derive that the position of key feature points (x, y) in the next frame is mobile (dx, dy), i.e. solution equationWherein, i indicate the surrounding side key feature points (x, y) row region (such as 3 × 3) the ith pixel point in, Ix、IyAnd ItIndicate gradient of the picture intensity I about picture space and time；Based on random sampling Consistency algorithm, the mobile abnormal key feature points in removal position, obtains average movement of the left point in picture planePosition of the object in the video frame is
S24: the projection imaging relationship α m of object is utilizedk=HZk, obtain the physical coordinates Z of objectk, with initial coordinate Z1Difference be moving displacement d of the target in time step kk；
S3: the axle distribution of given passing vehicle and axis weight extract traveling load information A from the video of acquisition；
S31: the video frame rate FPS of known vehicle body overall length L and acquisition, same observation station on bridge is passed through according to headstock, the tailstock Video frame number Ff、Fr, estimate vehicle pass-through Mean Speed v=LFPS/ (Fr-Ff)；
S32: it is distributed according to speed v and axle, estimates the shift position of each axle at any time, be then aggregated into mobile lotus Matrix A is carried, wherein elements A in matrixkmThe axle load acted on bridge unit m when time step k is indicated, if the unit is at this moment Without imposed load under spacer step, then Akm=0；
S4: according to the relationship of traveling load matrix A and structure measuring point displacement time-histories d, i.e. AIL=d solves structure bit Moving influences line IL.
The beneficial effects of the present invention are:
Compared with prior art, the present invention having the advantage that
1, the testing equipment being related to is simple, at low cost, it is only necessary to which video collector such as camera, mobile phone are equipped with video analysis Computer and the ancillary equipment such as tripod of program；It is easy to operate in test outdoors, without being installed at each measuring point of structure Sensor, on the daily operation of structure without influence；
2, compared with traditional displacement influence line measurement method, camera system proposed by the present invention can extract structure simultaneously The information of displacement and vehicular load position, the stationary problem not being related between sensor；
3, the method can provide the displacement influence line information along span length direction multi-measuring point simultaneously, and it is fixed to be conveniently used for structural damage The quantization of position and degree of injury.
Detailed description of the invention
Fig. 1 is the flow chart of the method for the present invention；
Fig. 2 is the arrangement of the camera system in the case of a single span railway bridge；
Fig. 3 is displacement time-histories of the railway bridge in the case where the train in one or four section compartments is current；
Fig. 4 is displacement influence line of the position at unit load (1N) in railway bridges.
Specific embodiment
Below in conjunction with technical solution, a specific embodiment of the invention is illustrated by the case of a single span railway bridge.
S1: camera is set up in place and acquires video, it is ensured that tested point is respectively positioned within the scope of camera fields of view in structure； The arrangement of camera system is shown in Fig. 2；
S2: being based on principle of computer vision, and displacement structure time-histories d is extracted from the video of acquisition；
S21: the monitoring objective positioned at span centre is selected in video initial frame, is located at m in picture plane1；
S22: according to the projection imaging relationship at four or more control point with monitoring objective in the same plane, meter Calculate plane homography H；
S23: being based on Lucas-Kanade optical flow algorithm, positions position m of the object in next video framek；
S24: the projection imaging relationship α m of object is utilizedk=HZk, obtain the physical coordinates Z of objectk, with initial coordinate Z1Difference be moving displacement d of the target in time step kk；Position is in the case where the train in one or four section compartments is current in bridge span Displacement time-histories is shown in Fig. 3；
S3: the axle distribution of given passing vehicle and axis weight extract traveling load information A from the video of acquisition；
S31: the video frame rate FPS of known vehicle body overall length L and acquisition, same observation station on bridge is passed through according to headstock, the tailstock Video frame number Ff、Fr, the current Mean Speed v=34.0km/h of train is estimated,；
S32: it is distributed according to speed v and axle, estimates the shift position of each axle at any time, be then aggregated into mobile lotus Carry matrix A；
S4: according to the relationship of traveling load matrix A and structure measuring point displacement time-histories d, i.e. AIL=d solves structure bit Moving influences line IL；The displacement influence line of gained span centre position is shown in Fig. 4.

Claims (3)

1. a kind of bridge structure displacement influence line measurement method based on computer vision technique, it is characterised in that: including following Step:
S1: camera is set up in place and acquires video, it is ensured that tested point is respectively positioned within the scope of camera fields of view in structure；
S2: being based on principle of computer vision, and displacement structure time-histories d is extracted from the video of acquisition；
S3: the axle distribution of given passing vehicle and axis weight extract traveling load information A from the video of acquisition；
S4: according to the relationship of traveling load matrix A and structure measuring point displacement time-histories d, i.e. AIL=d solves displacement structure shadow Ring line IL.
2. a kind of bridge structure displacement influence line measurement method based on computer vision technique according to claim 1, It is characterized by: the specific method of step S2 is:
S21: one or more monitoring objective is selected in video initial frame, is located at m in picture plane1；
S22: it according to the projection imaging relationship at four or more control point with monitoring objective in the same plane, calculates Plane homography H, wherein α m=HZ, α are the ratio of any scale, and m is two-dimensional coordinate of the control point in picture plane, Z For the actual physics coordinate at control point；
S23: being based on Lucas-Kanade optical flow algorithm, positions position m of the object in next video framek；Specific implementation process It is to be based on Shi-Tomasi Corner Detection, identify the key feature points (x, y) in target area；Vacation based on brightness constancy It is fixed, derive that the position of key feature points (x, y) in the next frame is mobile (dx, dy), i.e. solution equationWherein, i indicate the surrounding side key feature points (x, y) row region (such as 3 × 3) the ith pixel point in, Ix、IyAnd ItIndicate gradient of the picture intensity I about picture space and time；Based on random sampling Consistency algorithm, the mobile abnormal key feature points in removal position, obtains average movement of the left point in picture planePosition of the object in the video frame is
S24: the projection imaging relationship α m of object is utilizedk=HZk, obtain the physical coordinates Z of objectk, with initial coordinate Z1's Difference is moving displacement d of the target in time step kk。
3. a kind of bridge structure displacement influence line measurement method based on computer vision technique according to claim 1, It is characterized by: the specific method of step S3 is:
S31: the video frame rate FPS of known vehicle body overall length L and acquisition, the video that same observation station on bridge is passed through according to headstock, the tailstock Frame number Ff、Fr, estimate vehicle pass-through Mean Speed v=LFPS/ (Fr-Ff)；
S32: it is distributed according to speed v and axle, estimates the shift position of each axle at any time, be then aggregated into traveling load square Battle array A, wherein elements A in matrixkmThe axle load acted on bridge unit m when time step k is indicated, if the unit is in this time step Lower no imposed load, then Akm=0.
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112629896A (en) * 2020-09-16 2021-04-09 湘潭大学 Beam structure damage identification method based on horizontal support reaction influence line
CN112637553A (en) * 2020-11-25 2021-04-09 浙江大学 Bridge structure modal analysis method based on monitoring video
CN112710371A (en) * 2020-12-03 2021-04-27 湖南大学 Bridge dynamic weighing method and system based on real-time space position of vehicle
CN114937365A (en) * 2022-06-21 2022-08-23 东南大学 Bridge deck vehicle parameter identification method based on synchronous multi-vision sensor
GB2616322A (en) * 2022-03-03 2023-09-06 Univ Hefei Technology Computer vision-based dynamic bridge shape recognition method
CN118376162A (en) * 2024-06-20 2024-07-23 兰州理工大学 A method for measuring influence line of bridge structure displacement based on computer vision technology

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101297321A (en) * 2005-10-25 2008-10-29 布拉科成像S.P.A.公司 Method of registering images, algorithm for carrying out the method of registering images, a program for registering images using the said algorithm and a method of treating biomedical images to reduc
CN101358897A (en) * 2008-08-08 2009-02-04 重庆交通科研设计院 Influence line wireless remote automatic test equipment for bridge structure
JP5327796B2 (en) * 2009-02-25 2013-10-30 国立大学法人東京工業大学 Vehicle weight measuring system for vehicles passing through bridge, vehicle weight measuring method for vehicles passing through bridge, and computer program
CN104819813A (en) * 2015-04-29 2015-08-05 中南大学 Bridge influence line dynamic test method
CN105865735A (en) * 2016-04-29 2016-08-17 浙江大学 Method for bridge vibration testing and dynamic property recognition based on video monitoring
CN107588915A (en) * 2017-10-18 2018-01-16 厦门大学 A kind of Bridge Influence Line recognition methods and system
CN108491758A (en) * 2018-02-08 2018-09-04 深圳市睿灵创新科技开发有限公司 A kind of track detection method and robot
CN108760200A (en) * 2018-05-18 2018-11-06 苏交科集团股份有限公司 Vehicle it is non-at the uniform velocity by when Bridge Influence Line assay method
CN108844702A (en) * 2018-05-31 2018-11-20 南京东南建筑机电抗震研究院有限公司 The measuring method of Bridge Influence Line when vehicle at the uniform velocity passes through

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101297321A (en) * 2005-10-25 2008-10-29 布拉科成像S.P.A.公司 Method of registering images, algorithm for carrying out the method of registering images, a program for registering images using the said algorithm and a method of treating biomedical images to reduc
CN101358897A (en) * 2008-08-08 2009-02-04 重庆交通科研设计院 Influence line wireless remote automatic test equipment for bridge structure
JP5327796B2 (en) * 2009-02-25 2013-10-30 国立大学法人東京工業大学 Vehicle weight measuring system for vehicles passing through bridge, vehicle weight measuring method for vehicles passing through bridge, and computer program
CN104819813A (en) * 2015-04-29 2015-08-05 中南大学 Bridge influence line dynamic test method
CN105865735A (en) * 2016-04-29 2016-08-17 浙江大学 Method for bridge vibration testing and dynamic property recognition based on video monitoring
CN107588915A (en) * 2017-10-18 2018-01-16 厦门大学 A kind of Bridge Influence Line recognition methods and system
CN108491758A (en) * 2018-02-08 2018-09-04 深圳市睿灵创新科技开发有限公司 A kind of track detection method and robot
CN108760200A (en) * 2018-05-18 2018-11-06 苏交科集团股份有限公司 Vehicle it is non-at the uniform velocity by when Bridge Influence Line assay method
CN108844702A (en) * 2018-05-31 2018-11-20 南京东南建筑机电抗震研究院有限公司 The measuring method of Bridge Influence Line when vehicle at the uniform velocity passes through

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112629896A (en) * 2020-09-16 2021-04-09 湘潭大学 Beam structure damage identification method based on horizontal support reaction influence line
CN112637553A (en) * 2020-11-25 2021-04-09 浙江大学 Bridge structure modal analysis method based on monitoring video
CN112710371A (en) * 2020-12-03 2021-04-27 湖南大学 Bridge dynamic weighing method and system based on real-time space position of vehicle
CN112710371B (en) * 2020-12-03 2021-12-28 湖南大学 Bridge dynamic weighing method and system based on vehicle real-time spatial position
GB2616322A (en) * 2022-03-03 2023-09-06 Univ Hefei Technology Computer vision-based dynamic bridge shape recognition method
CN114937365A (en) * 2022-06-21 2022-08-23 东南大学 Bridge deck vehicle parameter identification method based on synchronous multi-vision sensor
CN118376162A (en) * 2024-06-20 2024-07-23 兰州理工大学 A method for measuring influence line of bridge structure displacement based on computer vision technology

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