Open Access

ARTICLE

Optimizing Computed Tomography Processing Parameters for Accurate Detection of Internal Defects in Reinforced Concrete

Yueshun Chen^1,2,*, Yupeng Zhou¹, Cao Yin³

1 School of Civil Engineering Architecture and Environment, Department of Architectural Engineering, Hubei University of Technology, Wuhan, 430068, China
2 Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China
3 Changjiang International Water Conservancy and Hydropower Engineering Construction Co., Ltd., Wuhan, 430040, China

* Corresponding Author: Yueshun Chen. Email:

Structural Durability & Health Monitoring 2025, 19(3), 575-592. https://doi.org/10.32604/sdhm.2024.057005

Received 05 August 2024; Accepted 22 October 2024; Issue published 03 April 2025

Abstract

Computed tomography (CT) can inspect the internal structure of concrete with high resolution, but improving the accuracy of measurements remains a key challenge due to the reliance on complex image processing and significant manual intervention. This study aims to optimize CT scanning parameters to enhance the accuracy of measuring crack widths and rebar volumes in reinforced concrete. Nine sets of specimens, each with varying rebar diameters and concrete cover thicknesses, were scanned before and after corrosion using an Optima CT scanner, followed by three-dimensional reconstructions using Avizo software. The effects of threshold values and “Erosion” coefficients on measurement accuracy were evaluated. The results demonstrated that an optimal lower threshold of 2950, combined with an ‘Erosion’ coefficient of 6, effectively limits the measurement error of rebar volumes to within 1%. The optimal threshold for measuring crack widths was influenced by the crack width, rebar diameter, and concrete cover thickness. Additionally, an optimized formula for determining crack measurement thresholds was proposed. This study significantly improves the accuracy of CT-based non-destructive testing (NDT) techniques, providing valuable insights for structural health monitoring (SHM).

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Keywords

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