Abstract
Hyperspectral inspection using imaging systems is becoming more and more important for quality control tasks in several industries, replacing well trained operators or established machine vision systems based on RGB-systems. Hyperspectral imaging (HSI) on thin coated substrates is challenging due to the high reflectivity of the substrates. Nevertheless, the thin films contribute to the spectral data and can be evaluated. Therefore, the performance of inspection systems can be increased significantly. However, the large amount of data generated by HSI has to be processed and evaluated for quality information about the product. In this paper, thin aluminum oxide (Al2O3) layers on stainless steel foil are investigated by HSI. These substrates can be used for the growth of vertically aligned carbon nanotubes (VA-SWCNT) for battery electrodes. HSI and spectral ellipsometry in combination with Partial Least Squares regression (PLS) was used to estimate the thickness of the Al2O3 layers and to calculate quality parameters for a possible monitoring process. The PLS model shows a R2CV of 0.979 and a RMSECV of 3.6.
Highlights
Visual inspection is an important tool for defect detection and quality control in industrial applications
Hyperspectral imaging (HSI) allows the acquisition of hyperspectral images, meaning that there is a complete wavelength spectrum for every pixel of an image
Normal hyperspectral starter kits are mostly equipped with some halogen lighting bulbs for direct lighting, but for thin film imaging the demand for a homogeneous and diffuse lighting must be met
Summary
Visual inspection is an important tool for defect detection and quality control in industrial applications. Visual inspection tasks are performed by trained operators and are liable to the subjectivity of the operators and the variability between the operators. This kind of inspection is relatively expensive due to the need for well-trained operators. For this reason, camera based systems are becoming more and more popular. Camera based systems are becoming more and more popular They allow for a non-destructive, objective, and complete inline quality control [1,2].
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