Improved digital photogrammetry technique for crack monitoring

Inspections to evaluate the safety, durability, and service life of aging infrastructure play an important role in determining the countermeasures that need to be taken, such as reinforcement, repair, and reconstruction. In infrastructure containing concrete, such as bridges and tunnels, crack widths and patterns on surfaces are two of the most important signs used to estimate durability. Current conventional techniques used for this purpose suffer from challenges such as tediousness, subjectivity, and high cost. Consequently, a new measurement technique that overcomes these challenges while measuring crack displacement with high accuracy and precision in aging civil engineering structures is needed. In this paper, we proposed a technique for measuring crack displacement using a digital camera image. In the proposed technique, reflective targets are established around both sides of a crack as gauges, and subsequent digital camera images of the targets are subjected to image processing to determine the displacements of the targets. These displacements can be measured using images captured from any arbitrary camera position. The results of experiments conducted to verify the efficacy of the proposed method show that crack displacements of less than 0.10mm can be measured with high accuracy and precision using digital images captured at a distance of 10.0m from the target, while less than 0.20mm changes in the tensile displacement of the crack can be measured from an image captured at 25.0m from the crack. Measurement results obtained from a tunnel are also presented to show that cracks in the walls of an actual tunnel can be identified through simple measurements. These measurements, taken over a period of one year, indicate that the tendency of crack displacement and slide movements are in close agreement.

[1]  J. Casas,et al.  Application of optical fiber distributed sensing to health monitoring of concrete structures , 2013 .

[2]  Arnaud Castel,et al.  Prediction of reinforcement corrosion using corrosion induced cracks width in corroded reinforced concrete beams , 2014 .

[3]  Risako Morimoto Estimating the benefits of effectively and proactively maintaining infrastructure with the innovative Smart Infrastructure sensor system , 2010 .

[4]  Taha Landolsi,et al.  Monitoring of strain induced by heat of hydration, cyclic and dynamic loads in concrete structures using fiber-optics sensors , 2014 .

[5]  Anders Heyden,et al.  Image analysis for monitoring of crack growth in hydropower concrete structures , 2009 .

[6]  Yoshiyuki Kojima,et al.  Tunnel maintenance in Japan , 2003 .

[7]  Kenneth R. White,et al.  Close-range photogrammetry applications in bridge measurement: Literature review , 2008 .

[8]  Tai-Tien Wang,et al.  Characterizing crack patterns on tunnel linings associated with shear deformation induced by instability of neighboring slopes , 2010 .

[9]  Kay Smarsly,et al.  Decentralized fault detection and isolation in wireless structural health monitoring systems using analytical redundancy , 2014, Adv. Eng. Softw..

[10]  Clive S. Fraser,et al.  A hybrid measurement approach for close-range photogrammetry , 2009 .

[11]  Giovanni Plizzari,et al.  Influence of concrete strength on crack development in SFRC members , 2014 .

[12]  Chang-Soo Han,et al.  Auto inspection system using a mobile robot for detecting concrete cracks in a tunnel , 2007 .

[13]  C. Fraser,et al.  An Operational Application of Automatic Feature Extraction: The Measurement of Cracks in Concrete Structures , 2002 .

[14]  Tai-Tien Wang,et al.  Application and validation of simple image-mosaic technology for interpreting cracks on tunnel lining , 2013 .

[15]  S. Miura,et al.  DEFORMATION MONITORING OF A SLOPE BY VISION METROLOGY , 2004 .

[16]  Yuzo Ohnishi,et al.  A study of the application of digital photogrammetry to slope monitoring systems , 2006 .

[17]  Eduardo Júlio,et al.  Characterisation of concrete cracking during laboratorial tests using image processing , 2012 .

[18]  Chollada Laofor,et al.  Defect detection and quantification system to support subjective visual quality inspection via a digital image processing: A tiling work case study , 2012 .

[19]  Yun Mook Lim,et al.  Monitoring Crack Changes in Concrete Structures , 2005 .

[20]  G. De Schutter Advanced monitoring of cracked structures using video microscope and automated image analysis , 2002 .

[21]  Zhicong Chen,et al.  A multi‐channel wireless connection system for structural health monitoring applications , 2011 .

[22]  Eduardo Júlio,et al.  Automatic crack monitoring using photogrammetry and image processing , 2013 .

[23]  C. Fraser,et al.  Monitoring the thermal deformation of steel beams via vision metrology , 2000 .

[24]  Uwe Hampel,et al.  Cascaded image analysis for dynamic crack detection in material testing , 2009 .

[25]  Shuji Hashimoto,et al.  Image‐Based Crack Detection for Real Concrete Surfaces , 2008 .

[26]  Luigi Barazzetti,et al.  Crack measurement: Development, testing and applications of an automatic image-based algorithm , 2009 .