Monitoring multiple geometrical dimensions in WAAM based on a multi-channel monocular visual sensor

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.

Automated summary

In this study, a novel multi-channel monocular vision sensor is designed to monitor multiple geometrical sizes in wire and arc additive manufacturing (WAAM). The sensor's accuracy is verified and it lays a solid foundation for high-precision control of multiple geometrical sizes in WAAM.