Evaluation of spalling in bridges using machine vision method

Eslam Mohammed Abdelkader, Osama Moselhi, Mohamed Marzouk, Tarek Zayed

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

The growing number of bridges and their deteriorated conditions on one hand and the budget squeeze for their repair and rehabilitation on the other call for automated detection of defects and smart methods for condition rating of these bridges. This paper presents a newly-developed standalone computer application for automated detection and evaluation of spalling severities in reinforced concrete bridges. The application is coded in C#.net and makes use of an early developed model for detection of surface defects. The method is applied in two tiers, in the first tier, a single-objective particle swarm optimization model is developed for detection of spalling based on Tsallis entropy function. The second tier is devised for evaluation of spalling severities. It generates a comprehensive representation of the bridge deck image using Daubechies discrete wavelet transform feature description algorithm. The second tier also encompasses a hybrid artificial neural networkparticle swarm optimization model for accurate prediction of spalling area; circumventing the drawbacks of the gradient descent algorithm. The developed method was tested using 60 images from three bridge decks in Montreal and Laval in Quebec, Canada. Results indicate significant superiority in area prediction accuracies; achieving mean absolute percentage error, mean absolute error and relative absolute error of 6.12%, 56.407 and 0.393, respectively. The developed method is expected to assist transportation agencies in performing more accurate condition assessment of concrete bridge decks and accordingly assist them in developing optimum maintenance plans.

Original languageEnglish
Title of host publicationProceedings of the 37th International Symposium on Automation and Robotics in Construction, ISARC 2020
Subtitle of host publicationFrom Demonstration to Practical Use - To New Stage of Construction Robot
PublisherInternational Association on Automation and Robotics in Construction (IAARC)
Pages1136-1143
Number of pages8
ISBN (Electronic)9789529436347
Publication statusPublished - 2020
Event37th International Symposium on Automation and Robotics in Construction: From Demonstration to Practical Use - To New Stage of Construction Robot, ISARC 2020 - Kitakyushu, Online, Japan
Duration: 27 Oct 202028 Oct 2020

Publication series

NameProceedings of the 37th International Symposium on Automation and Robotics in Construction, ISARC 2020: From Demonstration to Practical Use - To New Stage of Construction Robot

Conference

Conference37th International Symposium on Automation and Robotics in Construction: From Demonstration to Practical Use - To New Stage of Construction Robot, ISARC 2020
Country/TerritoryJapan
CityKitakyushu, Online
Period27/10/2028/10/20

Keywords

  • Artificial neural network
  • Daubechies discrete wavelet transform
  • Image
  • Reinforced concrete bridges
  • Single-objective optimization
  • Spalling
  • Tsallis entropy

ASJC Scopus subject areas

  • Artificial Intelligence
  • Civil and Structural Engineering
  • Human-Computer Interaction
  • Geotechnical Engineering and Engineering Geology

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