Infrared thermography for a quick construction progress monitoring approach in concrete structures

Construction progress monitoring ensures the construction project is consistent with the schedule and enables the detection of any deviations in the geometry and/or any variation in the schedule. The traditional progress monitoring requires specialized personnel to walk around on the construction site to manually collect data and verify the progress of activities, which is time consuming, costly and/or error prone. Image-based technology is effective for recording on-site data geospatially and chronologically. It has gained increasing attention in the construction field for progress monitoring, work space analysis and quality assurance. However, a notable downside of image processing is the light condition, particularly for noisy environments such as construction sites. Poor or undesirable ambient light conditions produce low quality images that significantly affect the accuracy of data extracted from related images and lead to a high level of errors. This paper presents an innovative approach based on thermal image analysis to overcome problems related to the image quality. Thirty preliminary tests and three case studies have been implemented to show the feasibility of the method. A range of improvement between 8 to 48% has been attained that confirms the great potential of thermal images to overcome the limitation of image-based approaches.

[1]  David Arditi,et al.  USING COLORS TO DETECT STRUCTURAL COMPONENTS IN DIGITAL PICTURES , 2002 .

[2]  P. Bison,et al.  Geometrical correction and photogrammetric approach in thermographic inspection of buildings , 2012 .

[3]  Danijel Rebolj,et al.  Automated continuous construction progress monitoring using multiple workplace real time 3D scans , 2018, Adv. Eng. Informatics.

[4]  Fei Dai,et al.  Comparison of Image-Based and Time-of-Flight-Based Technologies for Three-Dimensional Reconstruction of Infrastructure , 2013 .

[5]  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.

[6]  Mani Golparvar-Fard,et al.  Automated Progress Monitoring Using Unordered Daily Construction Photographs and IFC-Based Building Information Models , 2015, J. Comput. Civ. Eng..

[7]  Mojtaba Noghabaei,et al.  Real-Time Image Localization and Registration with BIM Using Perspective Alignment for Indoor Monitoring of Construction , 2019, J. Comput. Civ. Eng..

[8]  Nisha Puri,et al.  Bridge construction progress monitoring using lidar and 4D design models , 2020 .

[9]  Joaquín Martínez-Sánchez,et al.  Single image rectification of thermal images for geometric studies in façade inspections , 2012 .

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

[11]  David Hernández-López,et al.  Image-based thermographic modeling for assessing energy efficiency of buildings façades , 2013 .

[12]  Frédéric Bosché,et al.  Automated progress tracking using 4D schedule and 3D sensing technologies , 2012 .

[13]  R. Navon,et al.  Research in automated measurement of project performance indicators , 2007 .

[14]  Burcu Akinci,et al.  Technological assessment and process implications of field data capture technologies for construction and facility/infrastructure management , 2008, J. Inf. Technol. Constr..

[15]  Pedro Arias,et al.  Automation of thermographic 3D modelling through image fusion and image matching techniques , 2011 .

[16]  Raja Raymond Issa,et al.  Laser scanning technology and BIM in construction management education , 2016, J. Inf. Technol. Constr..

[17]  Lucía Díaz-Vilariño,et al.  Aerial oblique thermographic imagery for the generation of building 3D models to complement Geographic Information Systems , 2014 .

[18]  Hubo Cai,et al.  A graphical planning method for workspace-aware, four-dimensional modeling to assist effective construction planning , 2018, J. Inf. Technol. Constr..

[19]  David K. H. Chua,et al.  BIM-based Last Planner System tool for improving construction project management , 2019, Automation in Construction.

[20]  Mike Kagioglou,et al.  Automating progress measurement of construction projects , 2009 .

[21]  Rahul Joshi,et al.  Digital image-based plant phenotyping: a review , 2020, Korean Journal of Agricultural Science.

[22]  David J. Greenwood,et al.  Surveying the extent and use of 4D BIM in the UK , 2016, J. Inf. Technol. Constr..

[23]  Burcu Akinci,et al.  Automated Recognition of 3D CAD Objects in Site Laser Scans for Project 3D Status Visualization and Performance Control , 2009 .

[24]  Uwe Stilla,et al.  Automated progress monitoring based on photogrammetric point clouds and precedence relationship graphs , 2015 .

[25]  Lucía Díaz-Vilariño,et al.  Automatic thermographic and RGB texture of as-built BIM for energy rehabilitation purposes , 2013 .

[26]  Michael Zeiler,et al.  Modeling our world : the ESRI guide to geodatabase design , 1999 .

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

[28]  Feniosky Peña-Mora,et al.  Integrated Sequential As-Built and As-Planned Representation with D4AR Tools in Support of Decision-Making Tasks in the AEC/FM Industry , 2011 .

[29]  X. Zhang,et al.  Towards automated progress assessment of workpackage components in construction projects using computer vision , 2009, Adv. Eng. Informatics.

[30]  Andrey Dimitrov,et al.  Vision-based material recognition for automated monitoring of construction progress and generating building information modeling from unordered site image collections , 2014, Adv. Eng. Informatics.

[31]  Ioannis Brilakis,et al.  Concrete Column Recognition in Images and Videos , 2010, J. Comput. Civ. Eng..

[32]  I. Guerrero,et al.  Thermographic survey of two rural buildings in Spain , 2004 .

[33]  Mani Golparvar-Fard,et al.  End-to-end vision-based detection, tracking and activity analysis of earthmoving equipment filmed at ground level , 2019, Automation in Construction.

[34]  Ruodan Lu,et al.  Detection of Structural Components in Point Clouds of Existing RC Bridges , 2018, Comput. Aided Civ. Infrastructure Eng..

[35]  Yong K. Cho,et al.  As-Is 3D Thermal Modeling for Existing Building Envelopes Using a Hybrid LIDAR System , 2013 .

[36]  Liu Yang,et al.  Semi-automated generation of parametric BIM for steel structures based on terrestrial laser scanning data , 2020 .

[37]  Emanuele Trucco,et al.  Towards Automated Visual Assessment of Progress in Construction Projects , 2007, BMVC.

[38]  Youngjib Ham,et al.  An automated vision-based method for rapid 3D energy performance modeling of existing buildings using thermal and digital imagery , 2013, Adv. Eng. Informatics.

[39]  Changyoon Kim,et al.  4D CAD model updating using image processing-based construction progress monitoring , 2013 .

[40]  Hyoungkwan Kim,et al.  Using Hue, Saturation, and Value Color Space for Hydraulic Excavator Idle Time Analysis , 2007 .

[41]  Mani Golparvar-Fard,et al.  Visualization of construction progress monitoring with 4D simulation model overlaid on time-lapsed photographs , 2009 .