Fuzzy Granular computing and Dynamic Speckle Interferometry for the identification of different thickness of wet coatings

Abstract

Granular computing and fuzzy sets concepts are proposed here as a novel method to process speckle images stacks in a fast and natural way. Speckle images are the result of scanning a phenomenon that occurs when a beam of coherent light illuminates a sample in which there is any type of activity, not visible, which produces a pattern variable in time. This process has been applied to the drying of paints without contact. The proposed methodology evaluates the intensity variations, considering the uncertainties proper of the phenomenon, being necessary only few images to characterize the activity. In many manufacturing processes it is of great importance the automation of the thickness evaluation in fresh film coatings. Examples about drying of paint process and activity images in paint layers are presented. The results obtained show that this methodology requires less information and computational efforts than the usual methods and also allows almost real time processing. This granular computing approach should be of interest in automatic processes, adding quality test spots of fresh films to improve the performance of the painting tasks.