Automated dimensional quality assessment of precast concrete panels using terrestrial laser scanning

Abstract Precast concrete panels are a popular component for many construction projects in the world. To safeguard the overall quality of these construction projects, it is imperative to ensure that the dimensions and the quality of precast concrete panels conform to their design specifications. It is, hence, necessary to develop techniques that can quickly measure the dimensions and reliably assess the quality of precast concrete panels. Currently, such measurement tasks mostly rely on trained inspectors, and the process can be rather time consuming. To address these limitations, this study presents a fully automated and non-contact measurement technique that measures and assesses the dimensions and the quality of precast concrete panels using a terrestrial laser scanner (TLS). An edge and corner extraction technique is developed to estimate the dimensional properties of precast concrete panels from TLS scanning data. To increase the measurement accuracy, a compensation model is employed to account for the dimension losses caused by an intrinsic limitation of TLS. Experimental tests are performed on a laboratory specimen as well as actual precast concrete panels to validate the effectiveness of the proposed technique. The results demonstrate that the proposed technique can accurately and reliably measure the length, width and squareness of precast concrete panels in an automatic manner.

[1]  N. Yastikli Documentation of cultural heritage using digital photogrammetry and laser scanning , 2007 .

[2]  Wolfram Burgard,et al.  Robust 3D scan point classification using associative Markov networks , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[3]  Patrick X.W. Zou,et al.  The application of precast concrete technology in buildings and civil structures construction: Hong Kong experience , 2003 .

[4]  Tara C. Hutchinson,et al.  Improved image analysis for evaluating concrete damage , 2006 .

[5]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Ghang Lee,et al.  Process Model Perspectives on Management and Engineering Procedures in the Precast'Prestressed Concrete Industry , 2004 .

[7]  G. Priestnalla,et al.  Extracting urban features from LiDAR digital surface models , 2022 .

[8]  Benjamin A. Graybeal,et al.  Routine Highway Bridge Inspection Condition Documentation Accuracy and Reliability , 2004 .

[9]  Hojjat Adeli,et al.  A New Approach for Health Monitoring of Structures: Terrestrial Laser Scanning , 2007, Comput. Aided Civ. Infrastructure Eng..

[10]  Frédéric Bosché,et al.  Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction , 2010, Adv. Eng. Informatics.

[11]  Norbert Haala,et al.  REFINEMENT OF BUILDING FASSADES BY INTEGRATED PROCESSING OF LIDAR AND IMAGE DATA , 2007 .

[12]  Derek D. Lichti,et al.  Error Models and Propagation in Directly Georeferenced Terrestrial Laser Scanner Networks , 2005 .

[13]  M. Cree,et al.  Mixed pixel return separation for a full-field ranger , 2008, 2008 23rd International Conference Image and Vision Computing New Zealand.

[14]  Falko Kuester,et al.  Terrestrial Laser Scanning-Based Structural Damage Assessment , 2010, J. Comput. Civ. Eng..

[15]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[16]  Leonard Steinborn International Organization for Standardization ISO 9001:2000 Quality Management Systems — Requirements , 2004 .

[17]  Vladimir G. Kim,et al.  Shape-based recognition of 3D point clouds in urban environments , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[18]  Burcu Akinci,et al.  Characterization of Laser Scanners and Algorithms for Detecting Flatness Defects on Concrete Surfaces , 2011, J. Comput. Civ. Eng..

[19]  Antonio Galgaro,et al.  Contactless recognition of concrete surface damage from laser scanning and curvature computation , 2009 .

[20]  Henrik I. Christensen,et al.  Behaviour Coordination in Structured Environments , 2022 .

[21]  Burcu Akinci,et al.  Quantification of edge loss of laser scanned data at spatial discontinuities , 2009 .

[22]  Holly E. Rushmeier,et al.  The 3D Model Acquisition Pipeline , 2002, Comput. Graph. Forum.

[23]  Hans-Peter Seidel,et al.  Ridge-Valley Lines on Meshes via Implicit Surface Fitting , 2004 .

[24]  George Vosselman,et al.  Knowledge based reconstruction of building models from terrestrial laser scanning data , 2009 .

[25]  Barrie Dale,et al.  Quality Management Systems , 2015 .

[26]  P.-E Josephson,et al.  The causes and costs of defects in construction. A study of seven building projects , 1999 .

[27]  Martial Hebert,et al.  3-D measurements from imaging laser radars: how good are they? , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[28]  Stefan Gumhold,et al.  Feature Extraction From Point Clouds , 2001, IMR.

[29]  Debra F. Laefer,et al.  Flying Voxel Method with Delaunay Triangulation Criterion for Façade/Feature Detection for Computation , 2012, J. Comput. Civ. Eng..

[30]  David Coyne,et al.  Lateral Image Degradation in Terrestrial Laser Scanning , 2009 .

[31]  Markus H. Gross,et al.  Shape modeling with point-sampled geometry , 2003, ACM Trans. Graph..

[32]  Matthew J. Sottile,et al.  Curve and surface reconstruction: algorithms with mathematical analysis by Tamal K. Dey Cambridge University Press , 2010, SIGA.

[33]  C. Anumba DETECTING AIR POCKETS FOR ARCHITECTURAL CONCRETE QUALITY ASSESSMENT USING VISUAL SENSING , 2007 .

[34]  Burcu Akinci,et al.  A formalism for utilization of sensor systems and integrated project models for active construction quality control , 2006 .

[35]  Tony DeRose,et al.  Surface reconstruction from unorganized points , 1992, SIGGRAPH.

[36]  Wanqiu Liu,et al.  Application of 3D LIDAR Scan of a Bridge under Static Load Testing , 2010 .

[37]  C S Poon,et al.  Quantifying the waste reduction potential of using prefabrication in building construction in Hong Kong. , 2009, Waste management.

[38]  Derek D. Lichti,et al.  Error modelling, calibration and analysis of an AM–CW terrestrial laser scanner system , 2007 .

[39]  George Vosselman,et al.  Airborne and terrestrial laser scanning , 2011, Int. J. Digit. Earth.

[40]  Wolfram Burgard,et al.  Learning compact 3D models of indoor and outdoor environments with a mobile robot , 2003, Robotics Auton. Syst..

[41]  David Barber,et al.  Geomatics Techniques for Structural Surveying , 2004 .