Deformation Monitoring in Steel Arch Bridges Through Close-Range Photogrammetry and the Finite Element Method

Tasci, L.

doi:10.1111/ext.12022

Cited by 19 publications

(11 citation statements)

References 6 publications

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“…Sensor Size (mm × mm) 1 For coherency with the other works, only the forward overlap was reported here, although the paper also discussed the lateral overlap and their combined effect on the photogrammetric results. 2 Baseline and q were calculated for ψ = 60 • only, where the given depth of field had a lower effect on the final result [40].…”

Section: Papermentioning

confidence: 99%

“…Automatic photogrammetry based on Structure from Motion and Image Matching (SfM/IM) is a game-changer in many fields where 3D digitization is needed. The fields of application are very different, ranging from industrial applications [1], deformation monitoring of structures and bridges [2], forestry assessment [3], forensics [4], medicine [5], zooarchaeology [6], paleontology [7], special effects for cinema [8], and cultural heritage documentation [9], to cite a few.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Lateral Displacement in Automatic Close-Range Photogrammetry

Guidi

Malik

Micoli

2020

Sensors

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Based on the use of automatic photogrammetry, different researchers made evident that the level of overlap between adjacent photographs directly affects the uncertainty of the 3D dense cloud originated by the Structure from Motion/Image Matching (SfM/IM) process. The purpose of this study was to investigate if, in the case of a convergent shooting typical of close-range photogrammetry, an optimal lateral displacement of the camera for minimizing the 3D data uncertainty could be identified. We examined five different test objects made of rock, differing in terms of stone type and visual appearance. First, an accurate reference data set was generated by acquiring each object with an active range device, based on pattern projection (σz = 18 µm). Then, each object was 3D-captured with photogrammetry, using a set of images taken radially, with the camera pointing to the center of the specimen. The camera–object minimum distance was kept at 200 mm during the shooting, and the angular displacement was as small as π/60. We generated several dense clouds by sampling the original redundant sequence at angular displacements (nπ/60, n=1, 2, … 8). Each 3D cloud was then compared with the reference, implementing an accurate scaling protocol to minimize systematic errors. The residual standard deviation of error made consistently evident a range of angular displacements among images that appear to be optimal for reducing the measurement uncertainty, independent of each specimen shape, material, and texture. Such a result provides guidance about how best to arrange the cameras’ geometry for 3D digitization of a stone cultural heritage artifact with several convergent shots. The photogrammetric tool used in the experiments was Agisoft Metashape.

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Section: Papermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Lateral Displacement in Automatic Close-Range Photogrammetry

Guidi

Malik

Micoli

2020

Sensors

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“…In addition, its accuracy is high. Many studies have thus used CRP to measure structural deformations [46,49]. Owing to its accuracy and capacity to work without restrictions, CRP is a useful tool for providing intuitive building shape information.…”

Section: Close-range Photogrammetry-based 3d Modelsmentioning

confidence: 99%

Three-Dimensional Visualization Solution to Building-Energy Diagnosis for Energy Feedback

Lee

Park

et al. 2018

Energies

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Owing to the large ratio of consumption in the building sector, energy-saving strategies are required. Energy feedback is an energy-saving strategy that prompts consumers to change their energy-consumption behaviors. The strategy has been principally focused on providing energy-consumption information. However, the realization of energy savings using only consumption information remains limited. In this paper, a building-energy, three-dimensional (3D) visualization solution is thus proposed. The aim is to determine if the building manager will replace the facility after our recommendation to improve the building-energy efficiency derived from the energy information is given. This solution includes the process of diagnosing a building and providing a prediction of energy requirements if a building improvement effort is undertaken. Accurate diagnostic information is provided by real-time measurement data from sensors and building models using a close-range photogrammetry method, without depending on blueprints. The information is provided by employing visualization effects to increase the energy-feedback efficiency. The proposed strategy is implemented on two testbeds, and building diagnostics are performed accordingly. For the first testbed, the predicted energy improvement amount resulting from the facility upgrade is provided. The second testbed is provided with a 3D visualization of the energy information. The predicted value of energy improvement was derived from the improvement plan through energy diagnosis in each testbed as about 30% and as about 28%, respectively. Unlike existing systems, which provide only ambiguous data that lack quantitative information, this study is meaningful because it provides energy information with the aid of visualization effects before and after building improvements.

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“…Although there have been many studies on deformation monitoring for civil infrastructure while using various techniques and devices, e.g., tape extensometers [11,12], total stations [13,14], photogrammetry [15,16], and three-dimensional (3D) laser scanners [17,18], these methods have their own disadvantages for HSR track slab deformation monitoring: the tape extensometer can only be used to measure the distance changes relative to a fixed point and must be manipulated manually; total station is vulnerable to environmental interferences; and, the laser scanning technique has low accuracy with an error level of around ±5 mm. Therefore, this study will firstly develop a novel online SHM system that is enabled by fiber Bragg grating (FBG) technology (immunity to electromagnetic interference in HSR) for continuous and long-term monitoring of track slab deformation.…”

Section: Introductionmentioning

confidence: 99%

Measurement and Forecasting of High-Speed Rail Track Slab Deformation under Uncertain SHM Data Using Variational Heteroscedastic Gaussian Process

Wang

2019

Sensors

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Uncertainty in sensor data complicates the construction of baseline models for the measurement and forecasting (M&F) of high-speed rail (HSR) track slab deformation. Standard Gaussian process (GP) assumes a uniform noise throughout the input space. However, in the application to modelling of HSR structural health monitoring (SHM) data, this assumption can be unrealistic, because of its unique heteroscedastic uncertainty that is induced by dynamic train loading, electromagnetic interference, large temperature variation, and daily maintenance actions of railway track infrastructure. Therefore, this study firstly develops a novel online SHM system enabled by fiber Bragg grating (FBG) technology to eliminate electromagnetic interference on SHM data for continuous and long-term monitoring of track slab deformation, with the capacity of temperature self-compensation. To deal with different sources of uncertainty, the study explores Variational Heteroscedastic Gaussian Process (VHGP) approach while using variational Bayesian and Gaussian approximation for data modelling, estimation of the monitoring data uncertainty, and further data forecasting. The results demonstrate that the VHGP framework yields more robust regression results and the estimated confidence level can better depict the heteroscedastic variances of the noise in HSR data. Higher accuracy for both regression and forecasting is gained through VHGP and the position with maximum noise can be more accurately forecasted with a smooth varying confidence interval. Based on in-situ measurement data, the uncertainty levels for all sensors are estimated together with corresponding deformation profiles for the instrumented segment and three typical types of uncertainty are summarized during the M&F process of HSR track slab deformation.

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Deformation Monitoring in Steel Arch Bridges Through Close-Range Photogrammetry and the Finite Element Method

Cited by 19 publications

References 6 publications

Optimal Lateral Displacement in Automatic Close-Range Photogrammetry

Optimal Lateral Displacement in Automatic Close-Range Photogrammetry

Three-Dimensional Visualization Solution to Building-Energy Diagnosis for Energy Feedback

Measurement and Forecasting of High-Speed Rail Track Slab Deformation under Uncertain SHM Data Using Variational Heteroscedastic Gaussian Process

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