Evaluation of a novel video- and laser-based displacement sensor prototype for civil infrastructure applications

  1. Schumacher, Thomas
  2. Brown, Nicholas
  3. Vicente, Miguel A.
  1. 1 Portland State University
    info

    Portland State University

    Portland, Estados Unidos

    ROR https://ror.org/00yn2fy02

  2. 2 Universidad de Burgos
    info

    Universidad de Burgos

    Burgos, España

    ROR https://ror.org/049da5t36

Revista:
Journal of Civil Structural Health Monitoring

ISSN: 2190-5452 2190-5479

Año de publicación: 2021

Tipo: Artículo

DOI: 10.1007/S13349-020-00450-Z GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Journal of Civil Structural Health Monitoring

Objetivos de desarrollo sostenible

Referencias bibliográficas

  • American Association of State Highway and Transportation Officials. AASHTO LRFD Bridge Design Specifications. 2017
  • Shan B, Wang L, Huo X, Yuan W, Xue Z (2016) A bridge deflection monitoring system based on CCD. Adv Mater Sci Eng. https://doi.org/10.1155/2016/4857373
  • Hoag A, Hoult N, Take W, Moreu F, Le H, Tolikonda V (2017) Measuring displacements of a railroad bridge using DIC and accelerometers. Smart Struct Syst. https://doi.org/10.12989/sss.2017.19.2.225
  • Khuc T, Catbas FN (2017a) Computer vision-based displacement and vibration monitoring without using physical target on structures. Struct Infrastruct Eng 13(4):505–516
  • Khuc T, Catbas FN (2017b) Completely contactless structural health monitoring of real-life structures using cameras and computer vision. Struct Control Health Monit 24:e1852
  • Zhang D, Guo J, Lei X, Zhu C (2016) A high-speed vision-based sensor for dynamic vibration analysis using fast motion extraction algorithms. Sensors 16:572
  • Shariati A, Schumacher T, Ramanna N (2015) Eulerian-based virtual visual sensors to detect natural frequencies of structures. J Civil Struct Health Monit 5(4):457–468. https://doi.org/10.1007/s13349-015-0128-5
  • Schumacher T, Shariati A (2013) Monitoring of structures and mechanical systems using virtual visual sensors for video analysis: fundamental concept and proof of feasibility. Sensors 13:16551–16564
  • Yu J, Yan B, Meng X, Shao X (2016) Measurement of bridge dynamic responses using network-based real-time kinematic GNSS technique. J Surv Eng. https://doi.org/10.1061/(ASCE)SU.1943-5428.0000167
  • Ye XW, Dong CZ, Liu T (2016) A review of machine vision-based structural health monitoring: methodologies and applications. J Sensors. https://doi.org/10.1155/2016/7103039
  • Tian L, Pan B (2016) Remote bridge deflection measurement using an advanced video deflectometer and actively illuminated led targets. Sensors 16:1344
  • Feng D, Feng MQ, Ozer E, Fukuda Y (2015) A vision-based sensor for noncontact structural displacement measurement. Sensors 15:16557–16575
  • Shariati A, Schumacher T (2017) Eulerian-based virtual visual sensors to measure dynamic displacements of structures. Struct Control Health Monit. https://doi.org/10.1002/stc.1977
  • Lee JJ, Shinozuka M (2006) A vision-based system for remote sensing of bridge displacement. NDT&E Int 39:425–431
  • Yoneyama S, Ueda H (2012) Bridge deflection measurement using digital image correlation with camera movement correction. Mater Trans 53:285–290
  • Fuhr PL, Huston D, Beliveau JG, Spillman WB, Kajenski PJ (1991) Optical noncontact dual-angle linear displacement measurements of large structures. Exp Mech 31:185–188
  • Vicente M, Gonzalez D, Minguez J, Schumacher T (2018) A novel laser and video-based displacement transducer to monitor bridge deflections. Sensors 18:970
  • Feng DM, Feng MQ (2017) Experimental validation of cost-effective vision-based structural health monitoring. Mech Syst Signal Process 88:199–211
  • Feng DM, Feng MQ (2018) Computer vision for SHM of civil infrastructure: from dynamic response measurement to damage detection—a review. Eng Struct 156:105–117
  • Zhao X, Liu H, Yu Y, Zhu Q, Hu W, Li M, Ou J (2016) Displacement monitoring technique using a smartphone based on the laser projection-sensing method. Sens Actuators A Phys 246:35–47. https://doi.org/10.1016/j.sna.2016.05.012
  • Wu LJ, Casciati F, Casciati S (2014) Dynamic testing of a laboratory model via vision-based sensing. Eng Struct 60:113–125
  • Kohut P, Holak K, Martowicz A (2012) An uncertainty propagation in developed vision based measurement system aided by numerical and experimental tests. J Theor Appl Mech 50:1049–1061
  • Jeong Y, Park D, Park KH (2017) PTZ camera-based displacement sensor system with perspective distortion correction unit for early detection of building destruction. Sensors 17:430
  • Sładek J, Ostrowska K, Kohut P, Holak K, Gaska A, Uhl T (2013) Development of a vision based deflection measurement system and its accuracy assessment. Measurement 46:1237–1249
  • MATLAB (2019) version 9.6.0.1174912 (R2019a). The MathWorks Inc., Natick, Massachusetts. https://www.mathworks.com/
  • Huang L-K, Wang M-JJ (1995) Image thresholding by minimizing the measures of fuzziness. Pattern Recognit 28(1):41–51
  • Kromanis R, Xu Y, Lydon D, Martinez del Rincon J, Al-Habaibeh A (2019) Measuring structural deformations in the laboratory environment using smartphones. Front Built Environ 5:44. https://doi.org/10.3389/fbuil.2019.00044
  • Pan B, Qian K, Xie H, Asundi A (2009) Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review. Meas Sci Technol 20(6):062001
  • Pan B, Xie H, Xu B, Dai F (2006) Performance of sub-pixel registration algorithms in digital image correlation. Meas Sci Technol 17(6):1615
  • Quine BM, Tarasyuk V, Mebrahtu H, Hornsey R (2007) Determining star-image location: a new sub-pixel interpolation technique to process image centroids. Comput Phys Commun 177:700–706
  • Ding W, Gong D, Zhang Y, He Y (2014) Centroid estimation based on MSER detection and Gaussian Mixture Model. In: 2014 12th international conference on signal processing (ICSP), pp 774–779
  • Guizar-Sicairos M, Thurman ST, Fienup JR (2008) Efficient subpixel image registration algorithms. Opt Lett 33:156–158
  • Artese S, Achilli V, Zinno R (2018) Monitoring of bridges by a laser pointer. Dynamic measurement of support rotations and elastic line displacements: methodology and first test. Sensors 18(2):3381–3416
  • Park YS, Agbayani JA, Lee JH, Lee JJ (2016) Rotational angle measurement of bridge support using image processing techniques. J Sensors. https://doi.org/10.1155/2016/1923934
  • Artese G, Perrelli M, Artese S, Meduri S, Brogno N (2015) POIS, a low-cost tilt and position sensor: design and first tests. Sensors 15:10806–10824
  • American Society of Civil Engineers (2016) Minimum design loads and associated criteria for buildings and other structures (ASCE/SEI 7–16). American Society of Civil Engineers, Reston
  • MIDAS: Civil 2015, Gyeonggido, Korea, MIDAS information technology co., Ltd. Civil 2015 version 1.1. https://www.midasoft.com/bridge-library/civil/products/midascivil
  • Vicente M, González D, Mínguez J (2019) Spanish Patent No. ES 2684134 B2. “SISTEMA Y PROCEDIMIENTO PARA LA MONITORIZACIÓN DE ESTRUCTURAS”, Award Date: Oct. 3rd