Automatic Recognition and Analysis of Scanned Non-crimp Fabrics for Calculation of their Fluid Flow Permeability

Abstract

Automatic recognition of scanned images of distorted bi-axial fiber bundle arrangements is considered in order to obtain the overall permeability of the formed fiber network. Scanned images are pre-processed with color normalization followed by usage of a threshold to find the pixels belonging to the bundles, the threads keeping the bundles together, and the distinct gaps formed between the bundles. Since the scanned images virtually have a perfect grayscale, the intensity can be treated as a corresponding signal of the image. Next the regular character of the fiber network is investigated using Fourier analysis on the fiber bundles as well as on the threads. The direction, position, and spatial separation of the fiber bundle and the threads are obtained in this way. In order to recognize the bottom fiber bundle layer a fine structure technique is used. Small clusters falsely identified as belonging to the bottom bundle layer are removed by application of a threshold to the perimeter of the cluster. The gaps in the top bundle layer are identified more clearly in this way. Next, a local Fourier analysis is applied to obtain the local distortion of the bundle and the thread structure yielding the characteristic distribution of the gaps between the bundles. Finally the distribution of the width of the threads is obtained by simply identifying the minimal distance between the sides of the threads.

Keywords

composite materials non-crimp fabrics Fourier analysis

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