Calibration methodology of a vision system for measuring the displacements of long-deck suspension bridges

Santos, Carlos; Costa, C. Oliveira; Batista, Jorge

doi:10.1002/stc.438

Cited by 25 publications

(11 citation statements)

References 15 publications

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“…For stereoscopic view or multiple cameras, the triangulation method was used in [24,33,98] for 3D structural displacement measurement. A multi-camera arrangement provides more reliable results than a single view but the measurement quality has high dependency on the timesynchronisation of camera recordings.…”

Section: Application Reviewmentioning

confidence: 99%

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

Brownjohn

2017

J Civil Struct Health Monit

254

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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Section: Application Reviewmentioning

confidence: 99%

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

Brownjohn

2017

J Civil Struct Health Monit

254

125

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“…Chan et al [42] proposed a CCD camera-based method to measure the vertical displacement of bridges. Santos et al [43] performed the vision system calibration in structural displacement measurement of long-deck suspension bridges.…”

Section: Image Processing Algorithms As Illustrated Inmentioning

confidence: 99%

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

2016

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In the past two decades, a significant number of innovative sensing and monitoring systems based on the machine vision-based technology have been exploited in the field of structural health monitoring (SHM). This technology has some inherent distinctive advantages such as noncontact, nondestructive, long distance, high precision, immunity to electromagnetic interference, and large-range and multiple-target monitoring. A lot of machine vision-based structural dynamic measurement and structural state inspection methods have been proposed. Real-world applications are also carried out to measure the structural physical parameters such as the displacement, strain/stress, rotation, vibration, crack, and spalling. The purpose of this review article is devoted to presenting a summary of the basic theories and practical applications of the machine vision-based technology employed in structural monitoring as well as its systematic error sources and integration with other modern sensing techniques.

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“…Digital imaging is currently the predominant approach to detect the visible cracks on structures . In the studies of Jahanshahi et al, a brief survey has been presented on the impact and advancement of image‐based structural health monitoring (SHM).…”

Section: Introductionmentioning

confidence: 99%

An evaluation of image-based structural health monitoring using integrated unmanned aerial vehicle platform

Akbar

Qidwai

Jahanshahi³

2018

Struct Control Health Monit

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Increasing number of skyscrapers along with the large number of tall bridges in the urban setting throughout the world also increases the demand of robust and autonomously controlled structural health monitoring (SHM) in order to enhance the reliability of such structures and their surroundings. In this paper, an unmanned aerial vehicle (UAV)-based autonomous SHM system has been investigated, in which the images of the structural site captured by the UAV were stitched together to form the complete view of the structure. The image-stitching task has been done by using a well-known speeded up robust features (SURF)-based feature detection algorithm. The large number of features resulting from SURF are first reduced with random sample consensus algorithm and then the respective transformations are applied to align the images for final stitching. The comparison between the current and previous view of the structural site provides the structural differences. The proposed approach is tested on a sample structure in a lab with different possible realistic types of defects that are induced in the structure, and the performance of the proposed methodology is compared with the existing approaches. It has been shown that the proposed system can perform image stitching even if the UAV suffers angular displacement due to wind thrusts or calibration issues.The proposed approach has also been applied on a concrete structure, and the displacement detected on the column of the structure's backyard verified the feasibility for real-world SHM. KEYWORDS computer vision, progressive image stitching, speeded up robust features (SURF) algorithm, structural health monitoring, unmanned aerial vehicle (UAV)

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Calibration methodology of a vision system for measuring the displacements of long-deck suspension bridges

Cited by 25 publications

References 15 publications

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

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

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

An evaluation of image-based structural health monitoring using integrated unmanned aerial vehicle platform

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