Vision-based monitoring system for evaluating cable tensile forces on a cable-stayed bridge

Because of the characteristics of cable-supported bridges, the cable tensile force is considered a critical item in their maintenance. In particular, because the evaluation of the cable tensile force in a cable-stayed bridge is essential for understanding the general status of the structural system, identifying the initial values of this force in the construction of a bridge and then accurately predicting and comparing its estimated values during traffic use are very important tasks for the maintenance of a cable-stayed bridge. Therefore, in this study, a vision-based monitoring system that utilizes an image processing technique was developed to estimate the tensile force of stay cables during traffic use. A remotely controllable pan-tilt drive was installed in the developed vision-based monitoring system to estimate the forces on multiple cables using a single system. The use of a 20× electric zoom lens made it possible to achieve sufficient resolution to remotely derive the dynamic characteristics of the stay cables.

[1]  Jong-Jae Lee,et al.  Real-Time Displacement Measurement of a Flexible Bridge Using Digital Image Processing Techniques , 2006 .

[2]  Chih-Chen Chang,et al.  Nontarget Image-Based Technique for Small Cable Vibration Measurement , 2008 .

[3]  Sung-Wan Kim,et al.  Verification of Multi-point Displacement Response Measurement Algorithm Using Image Processing Technique , 2010 .

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

[5]  Elsa Caetano,et al.  A vision system for vibration monitoring of civil engineering structures , 2011 .

[6]  Mosbeh R. Kaloop,et al.  Bridge safety monitoring based-GPS technique: case study Zhujiang Huangpu Bridge , 2012 .

[7]  Taehyo Park,et al.  Estimation of cable tension force using the frequency-based system identification method , 2007 .

[8]  Aboelmagd Noureldin,et al.  Wavelet Transform for Structural Health Monitoring: A Compendium of Uses and Features , 2006 .

[9]  Yi-Qing Ni,et al.  Technology developments in structural health monitoring of large-scale bridges , 2005 .

[10]  Tadayuki Shimada,et al.  ESTIMATING METHOD OF CABLE TENSION FROM NATURAL FREQUENCY OF HIGH MODE , 1994 .

[11]  D. H. Wang,et al.  Wireless Monitoring of Cable Tension of Cable-Stayed Bridges Using PVDF Piezoelectric Films , 2001 .

[12]  Jerome P. Lynch,et al.  Development of an Automated Wireless Tension Force Estimation System for Cable-stayed Bridges , 2010 .

[13]  Hugh Alan Bruck,et al.  Digital image correlation using Newton-Raphson method of partial differential correction , 1989 .

[14]  T. Lardner,et al.  Experimental determination of frequencies and tension for elastic cables , 1998 .

[15]  Demeke B. Ashebo,et al.  Vertical Displacement Measurements for Bridges Using Optical Fiber Sensors and CCD Cameras — A Preliminary Study , 2009 .

[16]  S.-E. Chen,et al.  Nondestructive bridge cable tension assessment using laser vibrometry , 2005 .

[17]  S. Roux,et al.  Comparison of Local and Global Approaches to Digital Image Correlation , 2012 .

[18]  Ru Zhang,et al.  Smart elasto-magneto-electric (EME) sensors for stress monitoring of steel structures in railway infrastructures , 2011 .

[19]  G. Vendroux,et al.  Submicron deformation field measurements: Part 2. Improved digital image correlation , 1998 .

[20]  J. P. Lewis Fast Normalized Cross-Correlation , 2010 .

[21]  S. Roux,et al.  Digital Image Mechanical Identification (DIMI) , 2007, 0712.3918.

[22]  Jinlong Chen,et al.  Two-step digital image correlation for micro-region measurement , 2005 .

[23]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[24]  Pedro Arias,et al.  An innovative method for remote measurement of minimum vertical underclearance in routine bridge inspection , 2012 .

[25]  Hiroshi Zui,et al.  Practical Formulas for Estimation of Cable Tension by Vibration Method , 1980 .

[26]  Ming L. Wang,et al.  Application of EM stress sensors in large steel cables , 2005, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[27]  M. Sutton,et al.  Full-field speckle pattern image correlation with B-Spline deformation function , 2002 .

[28]  Jin-Hee Ahn,et al.  Structural dynamic displacement vision system using digital image processing , 2011 .