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2016
Conference Paper
Title
Online detection and categorisation of defects along carbon fibre production using a high resolution, high width line scan vision system
Abstract
During carbon fibre production as well as fabrication of follow up products such as preforms various defects affecting quality and performance of the finished product may occur. While numerous defects such as fuzz balls, roving twists or undulations are easy to identify, filament fractures or inhomogeneous binder distributions are challenging to detect and monitor. Typical carbon fibre filament diameters lie within the order of 5-7 μm in contrast to a production line width of 2-3 m as commonly observed in mass production, make the detection of fibre fractures difficult. Similarly, the online observation of binder distribution along a production process is a challenging issue. Thus high image resolution, a large scan width as well as a high image acquisition rate in accordance with the production speed are inevitably required for proper monitoring purposes. Based on the above, the current study focuses on a system developed to increase scan width at very high resolution. The limiting factor for image acquisition remains the data transfer rate. In this study, the scan width is maximized through the the use of a line scan camera and a specialized optic. This optical system allows the continuous capture and the increase of the monitored area with a magnitude of three compared to current optics, with no loss in acquisition rate. The software processes the acquired camera information for image segmentation. The algorithms then scan various sets of lines in the image and highlight specific Regions Of Interest (ROI). With a resolution in the order of a few microns, defects from filament fractures and small foreign particles up to fuzz balls can be clearly marked.
Language
English