ClosedLoop Control of Droplet Transfer in ElectronBeam Freeform Fabrication In the process of electronbeam freeform fabrication deposition, the surface of the deposit layer becomes rough because of the instability of the feeding wire and the changing of the thermal diffusion condition. This will make the droplet transfer distance change in the deposition process, and the droplet transfer cannot always be stable in the liquid bridge transfer state. It is easy to form a large droplet or make wire and substrate stick together, which makes the deposition quality worsen or even interrupts the deposition process. The current electronbeam freeform fabrication deposition is mostly openloop control, so it is urgent to realize the realtime and closedloop control of the droplet transfer and to make it stable in the liquid bridge transfer state. In this paper, a realtime monitoring method based on machine vision is proposed for the droplet transfer of electronbeam freeform fabrication. The detection accuracy is up to xc2xb1 0.08 mm. Based on this method, the measured droplet transfer distance is fed back to the platform control system in real time. This closedloop control system can stabilize the droplet transfer distance within xc2xb1 0.14 mm. In order to improve the detection stability of the whole system, a droplet transfer detection algorithm suitable for this scenario has been written, which improves the adaptability of the droplet transfer distance detection method by means of dilatationerosion, local minimum value suppression, and image segmentation. This algorithm can resist multiple disturbances, such as spatter, large droplet occlusion and so on.

Data Analysis Tool and Image Acquisition System for Linear Arc Weld Deposition Evaluation The ElectricArc Welding process is affected by several physical phenomena which have a direct impact on the final product quality. To understand and improve weld deposition is a key challenge to upgrade the overall metallic welding process. However, controlling the welding process of continuously fed melting wire electrode is still an open problem, which has not yet been solved. In order to study the phenomenon involved in the metallic transfer in linear welding, we employ a highspeed camera and laser lighting equipment to record the deposition images using two distinct imaging setups. Combining the image acquisition setup with voltage, current and wire speed data, we are able to obtain a dataset of distinct welding conditions, which allow us to observe critical aspects of the deposition. We present an acquisition methodology for generating a weld image dataset, as well as a software tool that makes possible to analyze, process and visualize each frame from recorded linear welding, providing per sample statistics and a framework to draw annotations of the due video. Through visual information and inferential statistics, we are able to identify how each parameter influences the weld of thick steel plates. Furthermore, we believe the tools provided will enable researchers to evaluate the deposition process and, thus, foster the development of hardware, software, and control techniques related to the field.