Abstract
Monitoring multiple geometrical dimensions is a crucial premise to realize precise control of layer size in wire and arc additive manufacturing (WAAM). Different from conventional single-target detection using a single sensor or multiple-target detection using multiple sensors, this study designs a novel multi-channel monocular vision sensor to monitor different geometrical sizes, i.e., current layer to nozzle distance, previous layer to nozzle distance, and layer width. A Marr-Hildreth algorithm is employed to extract boundaries of the molten pool and the previous layer. A homography matrix is solved for height calibration, and detected heights are introduced to assist layer width calibration. The sensor’s accuracy is verified via variable-size templates, and the maximum errors of detected height and width are 3.39% and 3.98%, respectively. Finally, the sensor is applied to monitor the layer size of a 5th-layered wall. This study lays a solid foundation for high-precision control of multiple geometrical sizes in WAAM.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
