Applications of Photogrammetry to Structural Assessment

Valença, Jónatas; Júlio, Eduardo; Araújo, Hélder

doi:10.1111/j.1747-1567.2011.00731.x

Cited by 66 publications

(51 citation statements)

References 6 publications

(11 reference statements)

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“…In this scope, photogrammetry enables to capture three dimensional information of constructions. Furthermore, photogrammetry can be used in situations where the application of traditional methods is difficult or even unviable, e.g, measure displacement during load tests (Fraser and Riedel, 2000;Jiang et al, 2008;Maas and Hampel, 2006;Valença et al, 2012).…”

Section: Photogrammetry: Precision and Accuracymentioning

confidence: 99%

“…In this case, static and dynamic tests were performed. After discarding the traditional monitoring, due to the difficulty of implementing, it was decided to use photogrammetry to measure the displacement of the bridge subjected to static load tests (Valença et al, 2012). For that purpose, a total of 83 targets were glued to external steel beam that supports the wooden deck.…”

Section: Bridge Load Testsmentioning

confidence: 99%

“…These are used as reference points and ground-truth constraints (Valença et al, 2012). Image acquisition of the network area including both sets, static and movable, targets in all the stages evaluated.…”

Section: Multi-station Approachesmentioning

confidence: 99%

“…In both cases, a multistation approach was applied (Valença et al, 2006) and the geometric model obtained was used to build the numerical model for structural analysis. The equipment and condition of the photographic survey is shown in Table 3.…”

Section: Geometric Survey Of Structuresmentioning

confidence: 99%

“…Nowadays, photogrammetry and laser-scanning are used to obtain geometric 3D information of built constructions, and methods based on processing of both RGB and multispectral images allows mapping the state of conservation of façades, applying classification algorithms to support the diagnosis of the state of conservation of built heritage (Crespo et al, 2010;Hemmleb et al, 2005;Kauffmann, 2002;Lerma et al, 2011;Remondino, 2011;Rinaudo et al, 2010 ;Valença et al, 2013b;Valença et al, 2012). Another emergent application of these methods consists in support the definition of maintenance plans, since built heritage requiring long-term preservation.…”

Section: Introductionmentioning

confidence: 99%

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Systems based on photogrammetry to evaluation of built heritage: tentative guidelines and control parameters

Valença

2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Technological innovations based on close-range imaging have arisen. The developments are related with both the advances in mathematical algorithms and acquisition equipment. This evolution allows to acquire data with large and powerful sensors and the fast and efficient processing of data. In general, the preservation of built heritage have applied these technological innovations very successfully in their different areas of intervention, namely, photogrammetry, digital image processing and multispectral image analysis. Furthermore, commercial packages of software and hardware have emerged. Thus, guidelines to best-practice procedures and to validate the results usually obtained should be established. Therefore, simple and easy to understand concepts, even for nonexperts in the field, should relate the characteristics of: (i) objects under study; (ii) acquisition conditions; (iii) methods applied; and (iv) equipment applied. In this scope, the limits of validity of the methods and a comprehensive protocol to achieve the required precision and accuracy for structural analysis is a mandatory task. Application of close-range photogrammetry to build 3D geometric models and for evaluation of displacements are herein presented. Parameters such as distance-to-object, sensor size and focal length, are correlated to the precision and accuracy achieved for displacement in both experimental and on site environment. This paper shows an early stage study. The aim consist in defining simple expressions to estimate the characteristics of the equipment and/or the conditions for image acquisition, depending on the required precision and accuracy. The results will be used to define tentative guidelines considered the all procedure, from image acquisition to final results of coordinates and displacements.

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Section: Photogrammetry: Precision and Accuracymentioning

confidence: 99%

Section: Bridge Load Testsmentioning

confidence: 99%

Section: Multi-station Approachesmentioning

confidence: 99%

Section: Geometric Survey Of Structuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Systems based on photogrammetry to evaluation of built heritage: tentative guidelines and control parameters

Valença

2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Method for assessing beam column joints in RC structures using photogrammetric computer vision

Valença

Carmo

2017

Struct Control Health Monit

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Summary The response of beam column joints is fundamental for structural analysis of reinforcement concrete frames, particularly, when subjected to dynamic actions. Monitoring the key parameters of those joints is essential to perform a detailed analysis of the structure. These are often difficult to obtain, and only a few sections in critical regions are assessed. High‐end technologies can bring huge advantages in such measurements. Methods based on computer vision have been applied to monitoring reinforced concrete structures with excellent results, considering the accuracy achieved and the large quantity of information recorded. In this paper, a new method, named “Photo‐Node,” based on photogrammetry and image processing is presented. Photo‐Node is a noncontact method used to directly monitoring concrete surfaces, developed to measure the relevant physical parameters of reinforcement concrete beam column joints during experimental tests. The method addresses several postprocessing features to evaluate joint rotation, joint distortion, principal directions and stresses, cracks pattern, and load path. Additionally, the critical sections of the beam, that is, the region adjacent to the joint where the formation of the plastic hinge is expected, can be also evaluated. Photo‐Node provides a large amount of data, which can be processed to properly assess the joints behaviour. The degree of discretisation achieved enables to identify behaviours impossible to detect using traditional and less discretised approaches. The application of the method showed promising and accurate results, proving to be an efficient and a wide‐ranging tool to be used in experimental programs.

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A vision‐based surface displacement/strain measurement technique based on robust edge‐enhanced transform and algorithms for high spatial resolution

Luo

Feng

et al. 2021

Structural Contr & Hlth

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Summary Measurement of two‐dimensional surface displacement/strain distributions can be crucial in monitoring important structures. Computer vision techniques have the potentials for measuring surface displacements/strains. Conventional digital‐image‐correlation (DIC)‐based computer vision techniques that have been applied in controlled conditions with artificially painted speckle patterns, however, have difficulties in robust measurement of structures' surface displacements against optical noises. Additionally, surface displacements obtained by DIC based on block‐resolution template matching have limited accuracy because of low spatial resolutions and low level of smoothness. Therefore, a new computer vision technique SurfaceVision is proposed for accurate and robust surface displacement/strain measurement to tackle simulated field environmental conditions by incorporating multiple novel algorithms. First, a gradient‐based edge‐enhanced transform (EET) originally developed for one‐point displacement tracking is extended for enabling robust surface displacement measurements against optical noises by manipulating gradient information rather than image intensities. Then, the improvement in the smoothness of surface displacements is enabled by incorporating EET with the iterative displacement optimization and the customized smart branching algorithms. Moreover, a novel pixel‐resolution measurement algorithm is proposed for increasing the spatial resolution of surface displacements. Finally, an original intuitive strain conversion algorithm is developed for converting surface displacements into surface strains based on the principle similar to strain‐gauge transducers. The performance of SurfaceVision is first validated in the numerical simulation and further demonstrated in the experiment of the four‐point bending test. And a new method developed for predicting crack formations before they appear on structure surfaces, based on analyses of surface displacements/strains, is demonstrated.

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Applications of Photogrammetry to Structural Assessment

Cited by 66 publications

References 6 publications

Systems based on photogrammetry to evaluation of built heritage: tentative guidelines and control parameters

Systems based on photogrammetry to evaluation of built heritage: tentative guidelines and control parameters

Method for assessing beam column joints in RC structures using photogrammetric computer vision

A vision‐based surface displacement/strain measurement technique based on robust edge‐enhanced transform and algorithms for high spatial resolution

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