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Title: Automatic Corrosion Classification and Quantification of Steel Reinforcing Bars Within Concrete Using Image Data Generated by an Inductive Sensor

Abstract

This paper presents a methodology to automatically distinguish and quantify the corrosion of reinforcing bars within concrete using images generated by an inductive sensor. The methodology comprises three stages; image generation using the inductive sensor, image segmentation and feature extraction and neural network object classification. Preliminary results have shown that the methodology has correctly classified all the corroded parts on the testing samples while estimated the corrosion rate correctly on 80% of the testing samples.

Authors:
; ; ;  [1]
  1. School of Electrical and Electronic Engineering, the University of Manchester, PO Box 88, Manchester M60 1QD (United Kingdom)
Publication Date:
OSTI Identifier:
20798225
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 820; Journal Issue: 1; Conference: Conference on review of progress in quantitative nondestructive evaluation, Brunswick, ME (United States), 31 Jul - 5 Aug 2005; Other Information: DOI: 10.1063/1.2184676; (c) 2006 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; CONCRETES; CORROSION; IMAGES; NEURAL NETWORKS; NONDESTRUCTIVE TESTING; STEELS

Citation Formats

Zaid, M., El-Madaani, F., Gaydecki, P., and Miller, G.. Automatic Corrosion Classification and Quantification of Steel Reinforcing Bars Within Concrete Using Image Data Generated by an Inductive Sensor. United States: N. p., 2006. Web. doi:10.1063/1.2184676.
Zaid, M., El-Madaani, F., Gaydecki, P., & Miller, G.. Automatic Corrosion Classification and Quantification of Steel Reinforcing Bars Within Concrete Using Image Data Generated by an Inductive Sensor. United States. doi:10.1063/1.2184676.
Zaid, M., El-Madaani, F., Gaydecki, P., and Miller, G.. Mon . "Automatic Corrosion Classification and Quantification of Steel Reinforcing Bars Within Concrete Using Image Data Generated by an Inductive Sensor". United States. doi:10.1063/1.2184676.
@article{osti_20798225,
title = {Automatic Corrosion Classification and Quantification of Steel Reinforcing Bars Within Concrete Using Image Data Generated by an Inductive Sensor},
author = {Zaid, M. and El-Madaani, F. and Gaydecki, P. and Miller, G.},
abstractNote = {This paper presents a methodology to automatically distinguish and quantify the corrosion of reinforcing bars within concrete using images generated by an inductive sensor. The methodology comprises three stages; image generation using the inductive sensor, image segmentation and feature extraction and neural network object classification. Preliminary results have shown that the methodology has correctly classified all the corroded parts on the testing samples while estimated the corrosion rate correctly on 80% of the testing samples.},
doi = {10.1063/1.2184676},
journal = {AIP Conference Proceedings},
number = 1,
volume = 820,
place = {United States},
year = {Mon Mar 06 00:00:00 EST 2006},
month = {Mon Mar 06 00:00:00 EST 2006}
}
  • Corrosion processes with time may cause cracking, delamination and finally catastrophic failure of concrete structures. From a safety aspect as well as economic reasons, it is necessary to monitor concrete structures to detect corrosion at its early stages utilizing non-destructive testing techniques. In this paper, a new monitoring technique using inductive scanning technology is presented. Results obtained using this technique are compared with the potential mapping data. The advantages and limitations of both techniques are discussed.
  • This paper demonstrates the feasibility of using solid-state magneto-inductive probes for detecting and imaging of steel reinforcing bars embedded within pre-stressed and reinforced concrete. Changes in the inductance of the sensor material are directly proportional to the strength of the measured magnetic field parallel to the sensor. Experimental results obtained by scanning steel bars specimens are presented. General performance characteristics and sensor output limitations are investigated by using different orientations, sensing distance, excitation intensity, bar sizes and geometries.
  • This paper addresses fundamental issues associated with the development of a real time inductive scanning system for non-destructive testing of pre-stressed and reinforced concrete. Simulated results has indicated that given a coil dimension of 300mmx300mmx2.5mm, 10mm rebars can be imaged down to a depth of 100 mm. Studies also indicate that the vertical component of the induced magnetic field is most favourable as it can be readily reconstructed to yield geometry and dimensional information pertaining to the rebar structure.
  • Thirty-one relatively large reinforced concrete slabs were fabricated in 1980 using either non-specification epoxy-coated reinforcing steel or calcium nitrite admixture with black (uncoated) steel. Their performance is compared with uncoated steel in concrete without admixtures. The slabs were placed in two lifts: the bottom lift consisted of a bottom mat of reinforcing steel in chloride-free concrete; and a top lift consisting of the top-mat rebars in concrete contaminated with various quantities of sodium chloride. All the electrical connections between the reinforcing mats were made exterior to the slabs so that the corrosion current flow could be monitored. A worst casemore » type of research design was used by specifying poor quality concrete, nonspecification epoxy-coated rebars, and good electrical coupling between the rebar mats. After curing, the slabs were mounted above ground and exposed to the environment of the Washington, D.C. location. They were periodically subjected to additional chloride exposure while being monitored for about 1 year to determine the corrosion rate. Selected slabs were then demolished to confirm the findings of the nondestructive testing.« less
  • The mathematical model for the chloride-induced corrosion of reinforcing steel in concrete is applied to analysis of the influence of the concrete quality (w/c ratio), concrete cover thickness and the degree of water saturation on the corrosion current density. The governing equations of electrical potential and oxygen transport through concrete, as well as the boundary conditions for the polarization on the cathodic part of steel surface are described. The numerical procedure based on the finite element and finite difference method is developed to solve the set of equations.