Artificial Vision System for the Automatic Measurement of Interfiber Pore Characteristics and Fiber Diameter Distribution in Nanofiber Assemblies

Abstract

Nanofiber structures are used in several technologies such as membranes, reinforced materials, textiles, catalysts, sensors, and biomedical materials. For all these applications, it is important to know the morphology of the assemblies, in particular their pore and fiber dimension distributions. However, the current methods used to measure pore sizes are all experimental and indirect; furthermore, the fiber diameter distribution is usually determined manually using a digital image of the nanofiber web. In this paper an artificial vision system is proposed to characterize the nanofiber web by automatically measuring several properties related to the interfiber pore distribution and to the nanofiber diameter distribution. The artificial vision system is characterized by a two-section structure: an image processing section and a property measurement section. The image processing section is centered on a multivariate image analysis procedure for the extraction of morphological features from the image. The property measurement section comprises an algorithm for interfiber pore area and pore morphology evaluation and one for fiber diameter distribution measurement that also accounts for the effect of perspective on the lower-level fiber diameters. Because the proposed artificial vision system is completely automatic, measurements can be taken without the need of any experimental setup and with no human intervention. Therefore, besides being fast and accurate, measurements do not suffer from repeatability issues. The ability of the proposed automatic system in characterizing the morphology of a thin nonwoven nanofiber fabric is demonstrated by application to polymer nanofiber membranes obtained by electrospinning