Research on precision automatic tool setting technology for KDP crystal surface damage mitigation based on machine vision
Research on precision automatic tool setting technology for KDP crystal surface damage mitigation based on machine vision
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基于机器视觉的KDP晶面损伤减缓精密自动对刀技术研究
DOI：
10.1016/j.jmapro.2021.02.012
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发表时间：
2021-04
影响因子：
6.2
通讯作者：
Xiaodong Yuan
中科院分区：
文献类型：
--
作者：
Linjie Zhao;Jian Cheng;Zhaoyang Yin;Hao Yang;Mingjun Chen;Xiaodong Yuan
迄今为止，微铣削已被认为是减轻激光聚变装置中使用的大口径KDP晶体表面损伤的最有前途的技术。然而，大口径KDP晶体表面仍有大量损伤有待减轻。此外，手动对刀的效率和精度较低，且容易因误操作而损坏KDP晶面。因此，本研究提出一种基于机器视觉的KDP晶体表面损伤减轻自动对刀技术。自动对刀包括通过图像测距实现的快速预对刀和通过微芯片检测实现的最终对刀。在快速预对刀过程中，获取微型铣刀的实时图像，通过图像测距获取刀尖与KDP晶面的距离。最后，将刀尖快速定位到距 KDP 晶体表面 20 μm 处。在最终对刀过程中，微型铣刀后退至距KDP晶体表面约50μm的距离，然后再检测微屑。因此，被微型铣刀覆盖的微芯片会暴露出来，出现在显微镜的视野中，从而提高微芯片的识别率。结果表明，自动对刀总时间为130 s，自动对刀精度优于1.359 μm。与手动对刀相比，本研究提出的基于机器视觉的自动对刀提高了自主研发的KDP晶体表面损伤缓解系统的安全性、效率和准确性。
Up to now, micro milling has been recognized as the most promising technique to mitigate the surface damage of large-aperture KDP crystal used in laser fusion facility. However, there are quantities of damages on the surface of large-aperture KDP crystal to be mitigated. Furthermore, the efficiency and accuracy of manual tool setting is relatively low, and it is easy to damage KDP crystal surface due to mis-operation. Therefore, an automatic tool setting technology for KDP crystal surface damage mitigation based on machine vision is proposed in this research. The automatic tool setting includes fast pre tool setting achieved by image ranging and final tool setting achieved by micro-chip detection. In the process of fast pre tool setting, real-time image of the micro milling cutter is obtained, and the distance between the tool tip and the KDP crystal surface is obtained by image ranging. Finally, the tool tip is quickly positioned 20 μm away from the KDP crystal surface. In the process of final tool setting, the micro milling cutter is retreated to a distance of about 50 μm away from the KDP crystal surface before detecting micro-chips. Therefore, the micro-chips covered by the micro milling cutter will be exposed and appear in the view field of microscope, so as to improve the micro-chip recognition rate. The results showed that the total time of automatic tool setting is 130 s, and the accuracy of automatic tool setting is better than 1.359 μm. Compared with manual tool setting, the automatic tool setting based on machine vision proposed in this research improves the safety, efficiency, and accuracy of independently developed mitigation system for KDP crystal surface damage.
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影响因子：
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