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<p>Concrete curing is a critical process that directly influences long-term strength and durability, yet conventional monitoring relies heavily on destructive tests that are time-consuming and limited in scalability. To address this challenge, the present study explores the application of ground-based hyperspectral remote sensing (HyRS) as a real-time, non-destructive approach for monitoring concrete curing and estimating compressive strength. Reflectance spectra were collected across 350–2500&#xa0;nm range for different concrete grades (M1–M6, and mixed datasets) at multiple curing intervals (Day 01, 07, and 28). The methodology incorporated spectral preprocessing, derivative analysis, band differencing, feature extraction, and principal component analysis (PCA) to capture hydration-related spectral dynamics. Analytical tools such as Pearson correlation mapping, spectral angle mapper (SAM), spectral information divergence (SID), and narrow-band ratio analysis were applied to validate key predictors of hydration and strength. Results revealed distinct spectral behaviors corresponding to hydration reactions, moisture loss, and material densification, with consistent increases in reflectance intensity observed in the near-infrared region. Specific spectral bands around 1420&#xa0;nm, 2200&#xa0;nm, and the 600–750&#xa0;nm visible range were identified as reliable indicators of hydration progress and strength development. PCA highlighted that variance at early curing ages is dominated by chemical and hydration differences, while at later stages it stabilizes in hydration bands. Overall, the study establishes hyperspectral sensing as a robust NDT framework for concrete monitoring, laying the groundwork for machine learning models to predict mechanical properties with high accuracy and for future deployment in mobile or drone-based structural health monitoring systems.</p>

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Real-time non-destructive monitoring of concrete curing and strength development using hyperspectral remote sensing

  • 期刊论文

  • 发表日期：

    2025年11月15日

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  • Ishtiaq Ahmed,
  • Umesh Kumar Sharma,
  • Pradeep Kumar Garg

摘要

Concrete curing is a critical process that directly influences long-term strength and durability, yet conventional monitoring relies heavily on destructive tests that are time-consuming and limited in scalability. To address this challenge, the present study explores the application of ground-based hyperspectral remote sensing (HyRS) as a real-time, non-destructive approach for monitoring concrete curing and estimating compressive strength. Reflectance spectra were collected across 350–2500 nm range for different concrete grades (M1–M6, and mixed datasets) at multiple curing intervals (Day 01, 07, and 28). The methodology incorporated spectral preprocessing, derivative analysis, band differencing, feature extraction, and principal component analysis (PCA) to capture hydration-related spectral dynamics. Analytical tools such as Pearson correlation mapping, spectral angle mapper (SAM), spectral information divergence (SID), and narrow-band ratio analysis were applied to validate key predictors of hydration and strength. Results revealed distinct spectral behaviors corresponding to hydration reactions, moisture loss, and material densification, with consistent increases in reflectance intensity observed in the near-infrared region. Specific spectral bands around 1420 nm, 2200 nm, and the 600–750 nm visible range were identified as reliable indicators of hydration progress and strength development. PCA highlighted that variance at early curing ages is dominated by chemical and hydration differences, while at later stages it stabilizes in hydration bands. Overall, the study establishes hyperspectral sensing as a robust NDT framework for concrete monitoring, laying the groundwork for machine learning models to predict mechanical properties with high accuracy and for future deployment in mobile or drone-based structural health monitoring systems.