Remote Inspection of Bridges with the Integration of Scanning Total Station and Unmanned Aerial Vehicle Data

Remote visual inspections are valuable tools for maintaining bridges in safe operation. In the case of old structures with incomplete documentation, the verification of dimensions is also an essential aspect. This paper presents an attempt to use a Scanning Total Station (STS) and Unmanned Aerial Vehicle (UAV) for the inspection and inventory of bridge dimensions. The STS’s measurements are conducted by applying two methods: the direct method using a total station (TS) and advanced geometric analyses of the collected point cloud. The UAV’s measurements use a Structure from Motion (SfM) method. Verification tests were conducted on a steel truss railway bridge over the largest river in Poland. The measurements concerned both the basic dimensions of the bridge and the details of a selected truss connection. The STS identified a significant deviation in the actual geometry of the measured connection and the design documentation. The UAV’s inspection confirmed these findings. The integration of STS and UAV technologies has demonstrated significant advantages, including STS’s high accuracy in direct measurements, with deviations within acceptable engineering tolerances (below a few mm), and the UAV’s efficiency in covering large areas, achieving over 90% compliance with reference dimensions. This combined approach not only reduces operating costs and enhances safety by minimizing the need for heavy machinery or scaffolding but also provides a more comprehensive understanding of the structural condition.

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Publication Details

Journal
Remote Sensing
Published
2024-11-08
DOI
https://doi.org/10.3390/rs16224176
Citations
7
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
5.84

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article

Remote Inspection of Bridges with the Integration of Scanning Total Station and Unmanned Aerial Vehicle Data

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7 citations
Remote Sensing
3D Surveying and Cultural Heritage
5.84
article

Remote Inspection of Bridges with the Integration of Scanning Total Station and Unmanned Aerial Vehicle Data

Rafael Cabral, Anna M. Rakoczy, Piotr Olaszek, Diogo Ribeiro, Ricardo Santos, Edgar Maciejewski
article en
7 citations

Abstract

Remote visual inspections are valuable tools for maintaining bridges in safe operation. In the case of old structures with incomplete documentation, the verification of dimensions is also an essential aspect. This paper presents an attempt to use a Scanning Total Station (STS) and Unmanned Aerial Vehicle (UAV) for the inspection and inventory of bridge dimensions. The STS’s measurements are conducted by applying two methods: the direct method using a total station (TS) and advanced geometric analyses of the collected point cloud. The UAV’s measurements use a Structure from Motion (SfM) method. Verification tests were conducted on a steel truss railway bridge over the largest river in Poland. The measurements concerned both the basic dimensions of the bridge and the details of a selected truss connection. The STS identified a significant deviation in the actual geometry of the measured connection and the design documentation. The UAV’s inspection confirmed these findings. The integration of STS and UAV technologies has demonstrated significant advantages, including STS’s high accuracy in direct measurements, with deviations within acceptable engineering tolerances (below a few mm), and the UAV’s efficiency in covering large areas, achieving over 90% compliance with reference dimensions. This combined approach not only reduces operating costs and enhances safety by minimizing the need for heavy machinery or scaffolding but also provides a more comprehensive understanding of the structural condition.

Remote SensingVol. 16(22)
Warsaw University of Technology (PL), Universidade do Porto (PT), Road and Bridge Research Institute (PL), Polytechnic Institute of Porto (PT)
Ministério da Ciência, Tecnologia e Ensino Superior, Narodowa Agencja Wymiany Akademickiej, Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 4%
3D Surveying and Cultural Heritage
5.84
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