On-line detection of oil on steel coils and thickness measurement using hyperspectral camera
The control of thickness homogeneity is a major concern in steel industry for quality issues. In the case of oil, an inhomogeneous coating on whole strip surface can create oxidation and lubrication trouble during coiling. Nowadays, different commercial solutions exist on the market (Light induced fluorescence, infrared gauges) but mainly for punctual measurements. The ability of new devices to characterize thin oil layers have been studied in this paper. This poster is focused on the study of spatial homogeneity for oil layer detection on steel surface for potential new online solution. The results presented in this paper confirm the interest of devices working in 3–5 μm spectral range to potentially answer to industrial needs.
Hyperspectral imaging for food quality analysis and control
Based on the integration of computer vision and spectrscopy techniques, hyperspectral imaging is a novel technology for obtaining both spatial and spectral information on a product. Used for nearly 20 years in the aerospace and military industries, more recently hyperspectral imaging has emerged and matured into one of the most powerful and rapidly growing methods of non-destructive food quality analysis and control. "Hyperspectral Imaging for Food Quality Analysis and Control" provides the core information about how this proven science can be practically applied for food quality assessment, including information on the equipment available and selection of the most appropriate of those instruments. Additionally, real-world food-industry-based examples are included, giving the reader important insights into the actual application of the science in evaluating food products. Presentation of principles and instruments provides core understanding of how this science performs, as well as guideline on selecting the most appropriate equipment for implementation. This title includes real-world, practical application to demonstrate the viability and challenges of working with this technology. It provides necessary information for making correct determination on use of hyperspectral imaging.
Determination of vinegar acidity by attenuated total reflectance infrared measurements through the use of second-order absorbance-pH matrices and parallel factor analysis.
Univariate (zero-order), multivariate (first-order) and multiway (second-order) calibrations were assayed for the determination of vinegar acidity using a mechanized procedure based upon vibrational spectroscopy and the emerging multicommutation methodology. The second-order methodology relies on the use of a flow system based on multicommutation and binary sampling. The flow network comprises a set of three-way solenoid valves, computer-controlled to provide facilities to handle the sample and to generate a time-dependent pH gradient using two carrier solutions. The procedure is based on the volumetric fraction variation approach that maintains the same volume of sample solution and dynamically varies its pH. The analysis of second-order absorbance-pH matrices was performed using parallel factor analysis (PARAFAC). Results were compared with first-order absorbance data analyzed with linear calibration and partial least squares regression (PLS) and they were employed for a discussion of the relative advantages of the applied chemometric tools. As excellent accuracy is obtained without the need of any sample pre-treatment, the procedure can be fully mechanized (i.e., by means of an auto-sampler device). Accuracy of the different strategies assayed was assessed by comparing the results achieved with those obtained by titration reference procedure.