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Abstract: A three-dimensional (3D) geometric model of a bridge plays an important role in inspection, assessment and management of the bridge. As most bridges were built after the second world war, 3D bridge models are rarely available. A recent development in laser scanning offers a cost-efficient method to capture dense, accurate 3D topographic data of the bridge. However, given the typical complexity of the bridge, a current workflow based commercial software to construct the bridge model still requires intensive labour work. This paper introduces a new approach to extract the point cloud of each surface of structural components of a slab/box beam bridge automatically in a sequential order from a superstructure to a substructure. The proposed method first employs a quadtree to decompose the point cloud of the bridge into two dimensional (2D) cells. Second, a kernel density estimation is used to separate a point cloud describing patches of surfaces within the cells. Subsequently, the cell- and voxel-based region growing are developed to segment patches within the cells/voxels for the superstructure and substructure, respectively. Moreover, knowledge of the bridge’s components (e.g. position, orientation, or shape) is introduced to allow the proposed method to identify criteria for filtering irrelevant objects, and to establish criteria for extracting the components. An experimental test shows the proposed method successfully extracts all surfaces of the bridge components.

Title: Structural deformation measurement-based laser scanning: Challenges and Lessons

Abstract. In construction projects, inspection of structural components mostly relies on typical measurements (e.g. measuring tapes, levelling or total stations). Additionally, with those methods, only a few points on the structure can be measured, and resulted inspection may not fully reflect the actual, detailed condition. Laser scanning is emerging a remote sensing technology to capture the structures’ surfaces in high details accurately and quickly. However, because of complex, massive data points acquired from the construction project, in practice, data processing is still manual work with support of computer aided program. To improve current workflows, this paper proposes a method automatically extracting structural components of the concrete building and subsequently inspects them in a term of deformation. The proposed method explores both spatial information of a point cloud and contextual knowledge of structures (e.g. orientation or shape). Additionally, based on the fundamental design of the structures, component’s boundaries are automatically extracted to establish un-deformed surfaces of the components for deformation measurement.

The bridge was scanned by Leica P40 with the sampling step of 6.3mm at a measuring range of 10m from 26 scan stations

The Constructie brug bridge is a concrete bridge with mix-vehicle and tram bridge with one span over a channel. The data points of the bridge were acquired using Leica ScanStation P40, from 9 stations (5 below, 2 on a top and 1 each side) with the sampling step 6.3mm at the measure range of 10.0m.

Title: Extracting Structural Components from Laser Scanning

Title: Automatic decomposition of bridge structural components from a terrestrial laser point cloud

Abstract: The development of laser scanning has offered a great opportunity to capture three-dimensional (3D) topographic information of objects’ surfaces highly accurately and efficiently. Particularly, a terrestrial laser scanner is able to acquire millions of points within a second at millimetre accuracy. This technology has been widely used in many civil engineering applications, including surveying, construction management, and infrastructure inspection. Traditionally, tank inspection was carried out on-site by physical inspectors with suitable measurement equipment (e.g. tapes, staffs and a total station). This approach, albeit the most common one, has many downsides: subjective results, slow and expensive procedure, the requirement of experienced and trained inspectors and close service of the tank. Additionally, all results are stored as hard copies, which leads to difficulties in tracking damage development and management. To mitigate these disadvantages, this paper proposes a method for (i) automatically extracting a point cloud of a tank wall from a massive data point, and (ii) evaluating the tank wall through its deformation.

The main goal of the short course of Geomatics 2019 is to provide participants with innovative practical and methodological skills to characterize complex terrain and object features using close- and near range remote sensing techniques.

Title: “Laser Scanning for Infrastructure Inspection & Assessment: Opportunities & Challenges”

Paper: “Laser scan-based structural assessment of wrought iron bridges: Guinness Bridge, Ireland” Engineering History and Heritage, 1-14, doi.org/10.1680/jenhh.17.00018

The bridge was scanned by Leica P40 with the sampling step of 6.3mm at a measuring range of 10m from 26 scan stations

Abstract: When aerial laser scanning (ALS) is deployed with targeted flight path planning, urban scenes can be captured in points clouds with both high vertical and horizontal densities to support a new generation of urban analysis and applications. As an example, this paper proposes a hierarchical method to automatically extract data points describing road edges, which are then used for reconstructing road edges and identifying accessible passage areas. The proposed approach is a cell-based method consisting of 3 main steps: (1) filtering rough ground points, (2) extracting cells containing data points of the road curb, and (3) eliminating incorrect road curb segments. The method was tested on a pair of 100m x 100m tiles of ALS data of Dublin Ireland’s city center with a horizontal point density of about 325 points/m²_. Results showed the data points of the road edges to be extracted properly for locations appearing as the road edges with the average distance errors of 0.07m and the ratio between the extracted road edges and the ground truth by 73.2%.

Abstract: Increasing traffic weights and aggressive environmental conditions may result in unexpected deterioration of a bridge’s components. Particularly, most bridges in Europe and US over half life span are affected by such impact. Structural deficiencies may cause partial or full collapse of bridges resulting in problems for human life, economy, society and environment. As such, deformation monitoring of the bridge’s components has high priority in bridge inspection and assessment. Laser scanning has been used to capture the three-dimensional (3D) topographic surface of structures accurately and efficiently, which can be subsequently used to measure change of the structures. This paper introduces three approaches called point-to-surface (P2S), point-to-cell (P2C) and cell-to-cell (C2C) to measure the deformation of a structure using laser scanning data. This study also investigates the impact of the quality of a point cloud and selected surface or cell size to the achieved accuracy of deformation detection, which will be demonstrated through an implementation to measure the bridge’s vertical clearance, which is the maximum vertical drop distance from the bottom of the bridge deck to the ground or water level.

The tower of the church was scanned by Leica P40 with the sampling step of 0.8mm at a measuring range of 10m from 10 scan stations.