In the process of electron-beam 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 electron-beam freeform fabrication deposition is mostly open-loop control, so it is urgent to realize the real-time and closed-loop control of the droplet transfer and to make it stable in the liquid bridge transfer state. In this paper, a real-time monitoring method based on machine vision is proposed for the droplet transfer of electron-beam freeform fabrication. The detection accuracy is up to ± 0.08 mm. Based on this method, the measured droplet transfer distance is fed back to the platform control system in real time. This closed-loop control system can stabilize the droplet transfer distance within ± 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 dilatation/erosion, local minimum value suppression, and image segmentation. This algorithm can resist multiple disturbances, such as spatter, large droplet occlusion and so on.
Keywords: closed-loop control; droplet transfer; electron-beam freeform fabrication; metal additive manufacturing.