Contactless recognition of concrete surface damage from laser scanning and curvature computation

A method conceived for automatic recognition of mass loss of concrete using data acquired by terrestrial laser scanner is presented here. The method is based on computation of mean and Gaussian curvatures of the surface and on piecewise comparison of the corresponding distributions, since these distributions strongly change if an area is affected by damage. This contactless damage recognition system, which could be applied together with other NDT techniques to provide a complete picture of the health of the observed structure, has been successfully applied to a concrete bridge.

[1]  Christophe Aubagnac,et al.  Comparison of NDT techniques on a post-tensioned beam before its autopsy , 2002 .

[2]  Kevin L. Rens,et al.  Ultrasonic Approach for Nondestructive Testing of Civil Infrastructure , 1997 .

[3]  Ahmet E. Aktan,et al.  ISSUES IN INFRASTRUCTURE HEALTH MONITORING FOR MANAGEMENT , 2000 .

[4]  S. Sumitro,et al.  Application of Smart 3-D Laser Scanner in Structural Health Monitoring , 2007 .

[5]  Helmut Pottmann,et al.  Industrial geometry: recent advances and applications in CAD , 2005, Comput. Aided Des..

[6]  Manfredo P. do Carmo,et al.  Differential geometry of curves and surfaces , 1976 .

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

[8]  B. Peeters,et al.  Stochastic System Identification for Operational Modal Analysis: A Review , 2001 .

[9]  D. Lichti,et al.  Angular resolution of terrestrial laser scanners , 2006 .

[10]  Hani Nassif,et al.  Comparison of laser Doppler vibrometer with contact sensors for monitoring bridge deflection and vibration , 2005 .

[11]  M. Crosetto,et al.  Deformation measurement using terrestrial laser scanning data and least squares 3D surface matching , 2008 .

[12]  Michael Forde,et al.  Application of infrared thermography to the non-destructive testing of concrete and masonry bridges , 2003 .

[13]  William C. Regli,et al.  A 3D object classifier for discriminating manufacturing processes , 2006, Comput. Graph..

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

[15]  Robert Bergevin,et al.  Detection and characterization of junctions in a 2D image , 2004, Comput. Vis. Image Underst..

[16]  Daniele Inaudi,et al.  Structural monitoring by curvature analysis using interferometric fiber optic sensors , 1998 .

[17]  Carlo Atzeni,et al.  Dynamic Monitoring of Bridges Using a High-Speed Coherent Radar , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Antonio Galgaro,et al.  Terrestrial laser scanner to detect landslide displacement fields: a new approach , 2007 .

[19]  Ehud Rivlin,et al.  A comparison of Gaussian and mean curvature estimation methods on triangular meshes of range image data , 2007, Comput. Vis. Image Underst..

[20]  Chen Xu,et al.  Synthesis of material drying history: phenomenon modeling, transferring and rendering , 2005, NPH.

[21]  Aly A. Farag,et al.  Surfacing Signatures: An Orientation Independent Free-Form Surface Representation Scheme for the Purpose of Objects Registration and Matching , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Ramesh C. Jain,et al.  Invariant surface characteristics for 3D object recognition in range images , 1985, Comput. Vis. Graph. Image Process..