Abstract

This project aims to develop a hyperspectral imaging approach for characterizing the mechanical and chemical properties of concrete and steel surfaces. A dual-sensor camera is used to collect images for mortar classification, mortar compressive strength assessment, Cl- concentration determination, and steel rebar and plate corrosion evaluation. Each pixel in an image includes spectral features ranging from 400 nm to 2500 nm in wavelength. For mortar samples, reflectance intensities at a wavelength of 1920 nm to 1980 nm, associated with the O-H chemical bond, were extracted and averaged to classify the types of mortars with K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms and predict their compressive strength with a regression equation. The reflectance intensity at 2258 nm was extracted to characterize Friedel’s salt concentration, which is correlated with the open circuit potential of steel rebar for corrosion evaluation. The possibility of steel corrosion was experimentally shown to increase with the characteristic reflectance intensity that in turn decreases linearly with the diffusion depth at a given corrosion state. The characteristic reflectance linearly increased with Cl- content up to 0.8 wt.%. For steel samples, spectral features were used to separate corroded, non-corroded, and transitional areas of steel plates.

Department(s)

Civil, Architectural and Environmental Engineering

Research Center/Lab(s)

INSPIRE - University Transportation Center

Sponsor(s)

Office of the Assistant Secretary for Research and Technology U.S. Department of Transportation 1200 New Jersey Avenue, SE Washington, DC 20590

Comments

Principal Investigator: Genda Chen, Ph. D., P. E.

Co-Principal Investigator: Hongyan Ma, P. E.

Grant #: USDOT # 69A3551747126

Grant Period: 11/30/2016 - 09/30/2024

Project Period: 03/001/2017 - 06/30/2023

The investigation was conducted under the auspices of the INSPIRE University Transportation Center.

Keywords and Phrases

Hyperspectral Imaging, Material Characterization

Report Number

INSPIRE UTC #012

Document Type

Technical Report

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2025 Missouri University of Science and Technology, All rights reserved.

Publication Date

June 30, 2023

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