Prediction of Grazing Incidence Focusing Mirror Imaging Quality Based on Accurate Modelling of the Surface Shape Accuracy for the Whole Assembly Process
Source abstract
Abstract
The key indicator of a grazing incidence focusing mirror’s imaging quality is its angular resolution, which is significantly influenced by its surface shape distribution error. In this paper, we propose a method for the prediction of grazing incidence focusing mirror imaging quality based on accurate modelling of the surface shape accuracy for the whole assembly process. Firstly, the three-dimensional surface shape distribution error of the inner surface of the focusing mirror is reconstructed based on measured point cloud data, and the changes in the surface shape induced by suspension gravity and the adhesive curing shrinkage force are obtained through simulation, and then an accurate geometric digital twin model based on the characterisation of its surface shape accuracy is established. Finally, a study on the quantitative prediction of the angular resolution of its imaging quality is performed. The results show that the surface shape error before assembly has the greatest influence on the imaging quality; the difference in angular resolution between the two suspension methods under the influence of gravity is approximately 2.1″, and the angular resolution decreases by about 4.2″ due to adhesive curing. This method can provide effective support for the prediction of the imaging quality of grazing incidence focusing mirrors.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Measurement and Metrology Techniques · Optical Systems and Laser Technology · Optical measurement and interference techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Beijing Institute of Control Engineering, Beijing 100190, China
Funding
National Natural Science Foundation of China
References (32)
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