Design and Implementation of a Vision Based In-Situ Defect Detection System of Automated Fiber Placement Process

Abstract

In this paper, an in-situ defect detection system is proposed for automated fiber placement (AFP) process monitoring. To acquire meaningful data about the laid-up tows, the design, manufacturing and integration of a flexible three degrees of freedom vision system to the AFP machine is proposed. An image segmentation algorithm is developed to locate and isolate defects in input images. The proposed algorithm utilizes Gabor filters to extract the desired texture features which is followed by an adaptive thresholding. Successful results with four of the main defect classes namely, foreign bodies, wrinkles, gaps and bridging, were obtained. This monitoring system can reduce time-consuming and expensive efforts of manual quality inspection and will significantly increase AFP process reliability.