In-line monitoring of the application weight of an adhesion promoter and the residual moisture content in textile finishing by hyperspectral imaging using a NIR camera

Abstract

Hyperspectral imaging was used for monitoring of both the application weight of an adhesion promoter for rubber applied to a polyester fabric by impregnation and the residual moisture in the fabric after drying at the end of the finishing process. A NIR camera with a spectral range from 1320 to 1900 nm was used for imaging. Quantitative data were derived from the spectra by chemometric methods using partial least squares (PLS) regression. Reference data for calibration and validation were determined by gravimetry. The root mean square errors of prediction (RMSEP) for the application weight and the moisture content were found to be 1.2 g/m² (for a probed range up to 25 g/m²) and 0.34 wt% (for water contents up to 10 wt%), respectively. Moreover, nonuniformities in both application weight and drying could be clearly uncovered. Mean values for application weight and moisture content obtained by averaging of the individual predictions from all pixels of each spectral image were found to show excellent correlation with the corresponding reference values from gravimetry. The results reveal that hyperspectral imaging with a NIR camera in combination with the PLS algorithm and adequate calibration is able to provide data with sufficient precision for in-line monitoring of both technical parameters and confirm the efficiency of this analytical approach for process control in technical textile converting.