Nontarget Stereo Vision Technique for Spatiotemporal Response Measurement of Line-Like Structures

Ji, Yao; Chang, Chin-Chen

doi:10.1061/(asce)0733-9399(2008)134:6(466)

Cited by 60 publications

(33 citation statements)

References 17 publications

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“…The feature of distributed sensing has been used in laboratory structures [17,19,29,30] for multistorey displacement measurement and system identification, as well as for cable vibration monitoring [31][32][33][34] aimed at the estimation of modal frequencies or cable tensions, but applications in bridge deformation measurement are limited, with only a few examples. [27,35] …”

Section: Distributed Sensingmentioning

confidence: 99%

A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge

Brownjohn

Kong

2018

Struct Control Health Monit

164

106

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SummaryVision-based monitoring receives increased attention for measuring displacements of civil infrastructure such as towers and bridges. Currently, most field applications rely on artificial targets for video processing convenience, leading to high installation effort and focus on only single-point displacement measurement, for example, at mid-span of a bridge. This study proposes a low-cost and non-contact vision-based system for multipoint displacement measurement based on a consumer-grade camera for video acquisition and a custom-developed package for video processing. The system has been validated on a cablestayed footbridge for deck deformation and cable vibration measurement under pedestrian loading. The analysis results indicate that the system provides valuable information about bridge deformation of the order of a few centimetres induced, in this application, by pedestrian passing. The measured data enable accurate estimation of modal frequencies of either the bridge deck or the bridge cables and could be used to investigate variations of modal frequencies under varying pedestrian loads. KEYWORDSbridge displacement, cable vibration, cable-stayed bridge, pedestrian loads, vision-based system | INTRODUCTIONStructural health monitoring is aimed at providing valuable information about structural performance and characterisation of structural defects to the asset owners, especially for those civil infrastructures beyond the design life. Vibrationbased modal tests are a common way for structural condition and serviceability assessment, providing a direct view about the structural stiffness, mass properties, and their distributions. [1] As well as for validating designs of civil structures, modal parameters extracted from vibration data obtained in short-term or long-term measurements are widely believed to have potential for identifying changes in structural condition or "damage." [2] The sensitivity of these parameters to damage depends on the nature of the damage, for example, local deterioration of material, for example, due to corrosion, may not be detectable against background effects of environmental variability, whereas boundary conditions are known to have a relatively strong effect, for example, fixity of bridge supports.[3]This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Distributed Sensingmentioning

confidence: 99%

A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge

Brownjohn

Kong

2018

Struct Control Health Monit

164

106

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“…Target patterns Determination of target location [30,90] Detecting the edges of line-shaped patterns and building image point correspondences among image sequences [90] or computing the cable motion from the distance between two identified edges [30] [12, 41,91,92] Detecting the edges of circular-shaped patterns through brightness thresholding or edge detection and computing the centroid coordinates for the circle [52] Detecting the edges of cross-shaped patterns through image gradient and computing the arithmetic mean of edge coordinates as the target location [53-55, 93, 94] Detecting four spots through brightness thresholding and computing the motions along the specified horizontal and vertical directions [11] Detecting grid dots by Harris corner detector and applying the image coordinates of grid dots for the estimation of camera extrinsic matrix [10] Detecting the edges of squares through brightness thresholding and computing the coordinates of the intersection point transformation relationship (output of camera calibration). In this case, the projection transformation is a fixed value or matrix without any update during the test.…”

Section: Referencesmentioning

confidence: 99%

“…accelerometers [40,85,106], velocimeters [41] and load cells [105]. Vision-based systems require no access to cables [16,30,40,85,86,90,105,106] and are capable of measuring the vibrations of multiple cables using a single camera [16,86,105,106] that is comparable to an array of accelerometers.…”

Section: Application Examplesmentioning

confidence: 99%

Review of machine-vision based methodologies for displacement measurement in civil structures

Brownjohn

2017

J Civil Struct Health Monit

232

125

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Vision-based systems are promising tools for displacement measurement in civil structures, possessing advantages over traditional displacement sensors in instrumentation cost, installation efforts and measurement capacity in terms of frequency range and spatial resolution. Approximately one hundred papers to date have appeared on this subject, investigating topics like system development and improvement, the viability on field applications and the potential for structural condition assessment. The main contribution of this paper is to present a literature review of vision-based displacement measurement, from the perspectives of methodologies and applications. Video-processing procedures in this paper are summarised as a three-component framework: camera calibration, target tracking and structural displacement calculation. Methods for each component are presented in principle, with discussions about the relative advantages and limitations. Applications in the two most active fields, bridge deformation and cable vibration measurement, are examined followed by a summary of field challenges observed in monitoring tests. Important gaps requiring further investigation are presented, e.g. robust tracking methods, non-contact sensing and measurement accuracy evaluation in field conditions.

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“…Technological developments in image sensors and optics lens have contributed to the rapidly increasing use of vision-based measurement methods as noncontact measurement methods in numerous research and industrial areas, such as vibration analysis, 4,5 condition monitoring, [6][7][8][9][10][11] human motion, 12,13 and underwater measurement. 14 With a relatively lower cost and better flexibility in structure, optical devices and cameras offer effective alternatives to noncontact equipment.…”

Section: Introductionmentioning

confidence: 99%

Vision-based displacement measurement sensor using modified Taylor approximation approach

et al. 2016

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, "Vision-based displacement measurement sensor using modified Taylor approximation approach," Opt. Eng. 55 (11) Abstract. The development of image sensors and optics lenses has contributed to the rapidly increasing use of vision-based methods as noncontact measurement methods in many areas. A high-speed camera system is developed to realize the displacement measurement in real time. Conventional visual measurement algorithms are commonly subjected to various shortcomings, such as complex processes, multiparameter adjustments, or integer-pixel accuracy. Inspired from the combination of block-matching algorithm and simplified optical flow, a motion estimation algorithm that uses modified Taylor approximation is proposed and applied to the vision sensor system. Simplifying integer-pixel searching with a rounding-iterative operation enables the modified algorithm to rapidly accomplish one displacement extraction within 1 ms and yield satisfactory subpixel accuracy. The performance of the vision sensor is evaluated through a simulation test and two experiments on a grating ruler motion platform and a steering wheel system of a forklift. Experimental results show that the developed vision sensor can extract accurate displacement signals and accomplish the vibration measurement of engineering structures.

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Nontarget Stereo Vision Technique for Spatiotemporal Response Measurement of Line-Like Structures

Cited by 60 publications

References 17 publications

A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge

A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge

Review of machine-vision based methodologies for displacement measurement in civil structures

Vision-based displacement measurement sensor using modified Taylor approximation approach

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