Energy Density Distribution and Temperature Closed-Loop Control in Electron Beam Processing

2009 ◽  
Vol 19 (2) ◽  
pp. 213-220
Author(s):  
Xuedong Wang ◽  
Qingyu Shi ◽  
Xin Wang
2021 ◽  
Vol 2064 (1) ◽  
pp. 012066
Author(s):  
V I Shin ◽  
P V Moskvin ◽  
M S Vorobyov ◽  
V N Devyatkov ◽  
N N Koval

Abstract The article presents the results of studies devoted to the study of the energy density distribution in the amplitude-modulated regime of electron beam generation. It is shown that in the first ≈ 50 μs of the duration of the beam current pulse, its spatial rearrangement occurs, due to the development of the arc discharge current. Thus, the rearrangement of the arc current, which develops from the axis of the system, leads to an axial diving of the emission current density and the beam current density on the target. With the development of the arc current, the energy density on the target on the axis of the system decreases and after ≈ 50 μs takes on a steady-state value, which can change only as a result of a change in the conditions for generating an electron beam or the transition to a modulated regime of electron beam generation. It has been experimentally shown using calorimetric measurements that the shape of the electron beam current pulse with its amplitude modulation with a pulse duration of more than 100 μs has little effect on the distribution of the beam energy density in the target region.


Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 923
Author(s):  
Shuhe Chang ◽  
Haoyu Zhang ◽  
Haiying Xu ◽  
Xinghua Sang ◽  
Li Wang ◽  
...  

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.


2012 ◽  
Vol 220 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Sandra Sülzenbrück

For the effective use of modern tools, the inherent visuo-motor transformation needs to be mastered. The successful adjustment to and learning of these transformations crucially depends on practice conditions, particularly on the type of visual feedback during practice. Here, a review about empirical research exploring the influence of continuous and terminal visual feedback during practice on the mastery of visuo-motor transformations is provided. Two studies investigating the impact of the type of visual feedback on either direction-dependent visuo-motor gains or the complex visuo-motor transformation of a virtual two-sided lever are presented in more detail. The findings of these studies indicate that the continuous availability of visual feedback supports performance when closed-loop control is possible, but impairs performance when visual input is no longer available. Different approaches to explain these performance differences due to the type of visual feedback during practice are considered. For example, these differences could reflect a process of re-optimization of motor planning in a novel environment or represent effects of the specificity of practice. Furthermore, differences in the allocation of attention during movements with terminal and continuous visual feedback could account for the observed differences.


Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 118-LB
Author(s):  
CAROL J. LEVY ◽  
GRENYE OMALLEY ◽  
SUE A. BROWN ◽  
DAN RAGHINARU ◽  
YOGISH C. KUDVA ◽  
...  

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 101-LB
Author(s):  
SUE A. BROWN ◽  
DAN RAGHINARU ◽  
BRUCE A. BUCKINGHAM ◽  
YOGISH C. KUDVA ◽  
LORI M. LAFFEL ◽  
...  

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