Now showing 1 - 10 of 24
  • Publication
    A Semi-Automatic Member Detection for Metal Bridges
    Terrestrial laser scanners (TLSs) are prominent non-contact instruments for acquiring highly detailed geometries of bridge components in only minutes. A TLS can be a strategic instrument for data collection for bridge inspection and documentation, because it can reduce significantly required field time and auxiliary equipment. To deploy a TLS in this field, a semi-automatic method for post-processing a point cloud for documentation of a historic metal bridge is proposed. In this work, generating 3D model of existing structural members and identifying connection characteristics are mainly of interest. The Guinness Bridge built in 1880s in Dublin, Ireland is presented as a case study for the proposed semi-automatic workflow.
  • Publication
    Documentation of Bridges by Terrestrial Laser Scanner
    Bridge structures are subjected to deterioration due to excessive usage, overloading, and aging material. For the last two decades, a significant amount research has been developed for collecting data for structural health monitoring. Yet, visual investigation with an on-site inspector remains the predominant method. This is true despite the highly subjective and time consuming aspects of this approach. Alternatively, terrestrial laser scanning can acquire surface details of structures quickly and accurately and is, thus, an emerging means to overcome the shortcomings of direct visual inspection. This paper presents a procedure for data collection for bridge inspection documentation and proposes a 'cell-based method' for determination of structure deterioration (involving vertical deformation and lateral distortion), as well as surface loss due to corrosion. The Guinness Bridge built in 1880s located in Dublin council, Ireland is selected as a case study to illustrate the efficacy of the proposed method.
  • Publication
    Automated Bridge Deck Evaluation through UAV Derived Point Cloud
    Imagery-based, three-dimensional (3D) reconstructions from Unmanned Aerial Vehicles (UAVs) hold the potential to provide a safer, more economical, and less disruptive approach for bridge inspection. This paper describes a methodology using a low-cost UAV to generate an imagery-based, dense point cloud for bridge deck inspection. Structure from motion (SfM) is employed to create a three-dimensional (3D) point cloud. Outlier data are removed through a density-based filtering method. Next, the unsupervised learning algorithm k-means and an object-based region growing algorithm are compared for accuracy with respect to bridge deck extraction. Last, an automatic pavement evaluation method is proposed to estimate the deck’s pavement condition. The procedure is demonstrated through an actual case study, in which a 3D point cloud of 16 million valid points was generated from 212 images. With that data set, the region growing method successfully extracted the deck area with an F-score close to 95%, while the unsupervised learning approach only achieved 76%. In the last, to evaluate the surface condition of the extracted pavement, a polynomial surface fitting method was designed to evaluate and visualise the damages.
  • Publication
    Application of Terrestrial Laser Scanner in Bridge Inspection: Review and an Opportunity
    (International Association for Bridge and Structural Engineering (IABSE), 2014-09-05) ;
    Heavy traffic and aggressive environmental conditions can cause unexpected bridge deterioration. Traditional condition evaluation is expensive. An alternative is Terrestrial laser scanning (TLS) which is a non-contact approach that safe, fast, and applicable to a range of weather conditions. This paper reviews applications of TLS on bridge measurement involving geometric documentation, surface defect determination, and corrosion evaluation, and crack identification. Currently, most post-processing of TLS is manual or within third party software. This paper discusses potential approaches to automatic post-processing.
  • Publication
    Using Terrestrial Laser Scanning for Dynamic Bridge Deflection Measurement
    Heavy vehicular traffic and aggressive environmental conditions can cause unexpected bridge deterioration, thus requiring periodic inspections to identify and assess possible defects. One indicator is the amount of vertical deflection that occurs during loading. Monitoring vertical bridge deflection through traditional surveying typically requires multiple instruments and extensive time in the field, along with their affiliated costs. A terrestrial laser scanner (TLS) can generate a million data points per second with millimeter level accuracy, thus offering the possibility of changing how vertical deflections of bridge girders are checked. This paper presents a preliminary investigation into using TLS to collecting vertical bridge displacements during dynamic loading. In this work, a point-surface based method is proposed to calculate the difference in elevation of a bridge girder at unloaded and loaded conditions. The technique is applied to the Loughbrickland Bridge in Northern Ireland.
  • Publication
    Framework for Bridge Inspection with Laser Scanning
    For the last two decades, a significant amount research has been developed for collecting data for bridge inspection. Yet, visual investigation with an on-site inspector remains the predominant method; however is the highly subjective and time consuming. Alternatively, terrestrial laser scanner (TLS) can acquire surface details of structures quickly and accurately and is, thus, an emerging means to overcome the shortcomings of direct visual inspection. This paper presents a framework of bridge inspection using TLS data, where a strategy of processing TLS data for deformation measurement, damage detection, and reconstruction of three dimension (3D) as-built models are explored. Demonstration of the application in bridge inspection is also provided.
  • Publication
    Micro vs. macro models for predicting building damage underground movements
    For over 30 years various micro and macro models have been used for analysing masonry, but no strong consensus within the structural engineering community exists as to usage. Selection remains driven by field scenarios, cost restrictions, and level of result detail needed. This paper contributes to this discussion by comparing micro and macro models of buildings subjected to excavation-induced ground movements. A smeared crack model is used to represent cracking in bricks and mortar joints, and the brick structure is modelled as an isotropic continuum. In the macro model, a homogeneous procedure employed is an alternative approach for determining mechanical properties of a basic cell. Results are compared to large-scale modelling work. Respective advantages and disadvantages are shown.
  • Publication
    Point Cloud Data Conversion into Solid Models via Point-Based Voxelization
    (American Society of Civil Engineers, 2013-05) ; ; ;
    Automated conversion of point cloud data from laser scanning into formats appropriate for structural engineering holds great promise for exploiting increasingly available aerially and terrestrially based pixelized data for a wide range of surveying-related applications from environmental modeling to disaster management. This paper introduces a point-based voxelization method to automatically transform point cloud data into solid models for computational modeling. The fundamental viability of the technique is visually demonstrated for both aerial and terrestrial data. For aerial and terrestrial data, this was achieved in less than 30 s for data sets up to 650,000 points. In all cases, the solid models converged without any user intervention when processed in a commercial finite-element method program.
      2810Scopus© Citations 68
  • Publication
    New Advances in Automated Urban Modelling from Airborne Laser Scanning Data
    Traditionally, urban models in many applications such as urban planning, disaster management, and computer games only require visual accuracy. However, more recently, updating urban infrastructure combined with the rise of mega-cities (i.e. those with populations over ten million) has motivated researchers and users to utilize city-scale models for engineering purposes (e.g. tracking pollution monitoring, optimizing solar panel placement), which necessitates high geometric accuracy. Currently, a major bottleneck lies in the cost of generating accurate, geo-spatially referenced models. This paper presents the evolution of some of the efforts to automatically produce such models. Specifically, recent advances in airborne laser scanning can rapidly acquire accurate, spatial data for large geographic areas in hours, but due to the size of the data sets, coupled with difficulties of capturing and portraying complex structures, many post-processing issues have only recently been addressed to a level sufficient to begin to facilitate automation, especially of building surface reconstruction. Automation is a critical step for further processing and utilization of airborne laser scanned data for engineering-based, urban modeling. This paper presents recent development of the methods for building detection and extraction, with an emphasis on patents and other contributions related to automated processing of airborne laser scanning data.
      568Scopus© Citations 8
  • Publication
    LiDAR point-cloud mapping of building façades for building energy performance simulation
    Current processes that create Building Energy Performance Simulation (BEPS) models are time consuming and costly, primarily due to the extensive manual inputs required for model population. In particular, generation of geometric inputs for existing building models requires significant manual intervention due to the absence, or outdated nature of available data or digital measurements. Additionally, solutions based on Building Information Modelling (BIM) also require high quality and precise geometrically-based models, which are not typically available for existing buildings. As such, this work introduces a semi-automated BEPS input solution for existing building exteriors that can be integrated with other related technologies (such as BIM or CityGML) and deployed across an entire building stock. Within the overarching approach, a novel sub-process automatically transforms a point cloud obtained from a terrestrial laser scanner into a representation of a building's exterior façade geometry as input data for a BEPS engine. Semantic enrichment is performed manually. This novel solution extends two existing approaches: (1) an angle criterion in boundary detection and (2) a voxelisation representation to improve performance. The use of laser scanning data reduces temporal costs and improves input accuracy for BEPS model generation of existing buildings. The approach is tested herein on two example cases. Vertical and horizontal accuracies of 1% and 7% were generated, respectively, when compared against independently produced, measured drawings. The approach showed variation in accuracy of model generation, particularly for upper floors of the test case buildings. However, the energy impacts resulting from these variations represented less than 1% of the energy consumption for both cases.
      254Scopus© Citations 15