Fibre-reinforced plastics (FRP) are particularly suitable for components where light-weight structures with advanced mechanical properties are required, e.g. for aerospace parts. Nevertheless, many manufacturing processes for FRP include manual production steps without an integrated quality control. A vital step in the process chain is the lay-up of the textile preform, as it greatly affects the geometry and the mechanical performance of the final part. In order to automate the FRP production, an inline machine vision system is needed for a closed-loop control of the preform lay-up. This work describes the development of a novel laser light-section sensor for optical inspection of textile preforms and its integration and validation in a machine vision prototype. The proposed method aims at the determination of the contour position of each textile layer through edge scanning. The scanning route is automatically derived by using texture analysis algorithms in a preliminary step. As sensor output a distinct stage profile is computed from the acquired greyscale image. The contour position is determined with sub-pixel accuracy using a novel algorithm based on a non-linear least-square fitting to a sigmoid function. The whole contour position is generated through data fusion of the measured edge points. The proposed method provides robust process automation for the FRP production improving the process quality and reducing the scrap quota. Hence, the range of economically feasible FRP products can be increased and new market segments with cost sensitive products can be addressed.

Date Published: 28 April 2008
PDF: 12 pages
Proc. SPIE 7003, Optical Sensors 2008, 70031I (28 April 2008); doi: 10.1117/12.779005

Published in SPIE Proceedings Vol. 7003:
Optical Sensors 2008
Francis Berghmans; Patrick P. Meyrueis; Thomas P. Pearsall; Anna Grazia Mignani; Antonello Cutolo, Editor(s)