Mapping of Bead Geometry in Wire Arc Additive Manufacturing Systems Using Passive Vision

This work addresses the online extraction of the geometry characteristics (width and centerline) of deposited beads with monocular cameras for wire arc additive manufacturing (WAAM). To enable online measurement and feature extraction from captured images, an adaptive threshold is used for segmentation, a Canny algorithm for edge detection, a Hough-line transform for feature identification of the bead edges, and a filtering step to attenuate the low signal-to-noise ratios of deposition processes. Online measurements are performed in single-bead and layer (multi-bead) scenarios. The proposed vision-based solution is experimentally implemented in a WAAM robotic system composed of a welding torch, a Kuka KR90 robot arm, a power source, wire feeder, and a passive monocular camera. Experimental results illustrate the performance and effectiveness of the proposed visual-based methodology.

Automated summary

This study presents a method for online extraction of geometry characteristics of deposited beads in WAAM using monocular cameras. The method involves measurement and feature extraction using various image processing algorithms, including segmentation and edge detection. Experimental results demonstrate the performance and effectiveness of the proposed method.