Fundamental study on estimation method of chloride ion concentration in concrete using near-infrared spectroscopy and chemometrics

Abstract

Recently, near-infrared spectroscopy has been attracting attention as an efficient method for evaluating chloride ion concentrations in concrete structures. In previous studies, estimation was mainly based on regression using absorbance at specific wavelengths. In this study, we conducted a basic study on a regression estimation method using chemometric data over the entire absorbance spectrum to establish a general-purpose method for estimating chloride ion concentrations by near-infrared spectroscopy. Specifically, we verified the general data preprocessing methods used in chemometrics, the applicability of principal component regression, and the effects of various preprocessing parameters on estimation accuracy. As a result, we found that estimation with high accuracy is possible using multiple principal component scores, and that the impact of preprocessing parameters on estimation accuracy is significant, so it is necessary to appropriately derive the optimal variables.