A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Imaging and Laser Scanning–Based Noncontact Deflection Monitoring Technique for Timber Railroad Bridges
https://orcid.org/0000-0003-3144-319X
This study developed a noncontact deflection monitoring technique using terrestrial laser scanner (TLS) and images for faster, safer, and efficient 2D/3D bridge deflection measurements. The technique was applied to assess the serviceability performance of two timber trestle railroad bridges located in Florida and validated based on bridge deflections from deflectometers. A key challenge includes extracting control points that are visible both in images and TLS data due to different modalities of the data. Hence, this study presents a method of extracting linear features from both images and TLS data. The camera pose was derived from images and TLS data by using a linear feature-based registration algorithm. The deformations in the structure were then detected by measuring the points of interest for different loads. There are several unique contributions of the study. First, there is no requirement for the use of targets which improves the safety of bridge engineers. Second, it is a relatively cost-effective technique for obtaining bridge deflections due to moving train loads, as the use of a laser scanner as part of the noncontact technique is only once in a lifetime for a given bridge. Alternatively, total stations can also be used to capture linear features. Finally, this technique produced accurate deflection measurements using a linear feature-based registration technique. This study found that the noncontact deflection monitoring technique agrees well with actual deformations observed from deflectometers.
Imaging and Laser Scanning–Based Noncontact Deflection Monitoring Technique for Timber Railroad Bridges
https://orcid.org/0000-0003-3144-319X
This study developed a noncontact deflection monitoring technique using terrestrial laser scanner (TLS) and images for faster, safer, and efficient 2D/3D bridge deflection measurements. The technique was applied to assess the serviceability performance of two timber trestle railroad bridges located in Florida and validated based on bridge deflections from deflectometers. A key challenge includes extracting control points that are visible both in images and TLS data due to different modalities of the data. Hence, this study presents a method of extracting linear features from both images and TLS data. The camera pose was derived from images and TLS data by using a linear feature-based registration algorithm. The deformations in the structure were then detected by measuring the points of interest for different loads. There are several unique contributions of the study. First, there is no requirement for the use of targets which improves the safety of bridge engineers. Second, it is a relatively cost-effective technique for obtaining bridge deflections due to moving train loads, as the use of a laser scanner as part of the noncontact technique is only once in a lifetime for a given bridge. Alternatively, total stations can also be used to capture linear features. Finally, this technique produced accurate deflection measurements using a linear feature-based registration technique. This study found that the noncontact deflection monitoring technique agrees well with actual deformations observed from deflectometers.
Imaging and Laser Scanning–Based Noncontact Deflection Monitoring Technique for Timber Railroad Bridges
https://orcid.org/0000-0003-3144-319X
This study developed a noncontact deflection monitoring technique using terrestrial laser scanner (TLS) and images for faster, safer, and efficient 2D/3D bridge deflection measurements. The technique was applied to assess the serviceability performance of two timber trestle railroad bridges located in Florida and validated based on bridge deflections from deflectometers. A key challenge includes extracting control points that are visible both in images and TLS data due to different modalities of the data. Hence, this study presents a method of extracting linear features from both images and TLS data. The camera pose was derived from images and TLS data by using a linear feature-based registration algorithm. The deformations in the structure were then detected by measuring the points of interest for different loads. There are several unique contributions of the study. First, there is no requirement for the use of targets which improves the safety of bridge engineers. Second, it is a relatively cost-effective technique for obtaining bridge deflections due to moving train loads, as the use of a laser scanner as part of the noncontact technique is only once in a lifetime for a given bridge. Alternatively, total stations can also be used to capture linear features. Finally, this technique produced accurate deflection measurements using a linear feature-based registration technique. This study found that the noncontact deflection monitoring technique agrees well with actual deformations observed from deflectometers.
Imaging and Laser Scanning–Based Noncontact Deflection Monitoring Technique for Timber Railroad Bridges
Pract. Period. Struct. Des. Constr.
Nagarajan, Sudhagar (author) / Srikanth, Ishwarya (author) / Khamaru, Satarupa (author) / Arockiasamy, Madasamy (author)
2023-02-01
Article (Journal)
Electronic Resource
English
Brown's timber railroad bridges
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Research for Better Timber Railroad Bridges
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Evaluation and Testing of Timber Railroad Bridges
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Dynamic Assessment of Timber Railroad Bridges Using Displacements
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