In-line monitoring of the thickness distribution of adhesive layers in black textile laminates by hyperspectral imaging

Abstract

Near-infrared (NIR) hyperspectral imaging was used for in-line monitoring of thickness and homogeneity of hot melt adhesive layers inside laminates made up of black polyester textiles. Reflection spectra were found to correlate with the thickness of the adhesive layers inside the laminates. Quantitative values were obtained from the spectra using data processing tools based on multivariate techniques such as partial least squares (PLS) regression. The prediction error (RMSEP) was found to be about 6 gm−2. This precision is regarded to be sufficient for applications in process control. Calibration models were used for spectral imaging of textile laminates in order to demonstrate the power of the method for quantitative in-line monitoring of the application weight and its spatial distribution across the samples. The developed measuring approaches can be used for continuous large-area analysis in technical lamination processes, which qualifies them for quality and process control in field-scale.