Study on model simulation design based on open CASCADE platform

Mingxia Zhao

doi:10.1117/12.2627076

2 March 2022 Study on model simulation design based on open CASCADE platform

Mingxia Zhao

Proceedings Volume 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021); 1215814 (2022) https://doi.org/10.1117/12.2627076
Event: 2021 International Conference on Computer Vision and Pattern Analysis, 2021, Guangzhou, China

Abstract

CAD-based geometric design has been widely used in various industries in the society. With the continuous improvement of design complexity, higher requirements are placed on the model simulation design of high-precision and high-confidence. The paper analyzes the simulation process of 3D model and improves the feature extraction method in the process based on the research of Open CASCADE platform. Firstly, the CAD platform geometry model is used to develop the model concept map, and then the model's three-view projection map is used to extract feature information; meanwhile, the complex surface adjustment and description are used to represent the model feature information. Finally, the graph feature vector obtained by the complex facet and transformation is calculated by using the maximum and minimum approximations as the distance between the feature references so as to evaluate the similarity between the models. The experiment have shown that the projection mapping of complex surface adjustment can accurately identify the fluctuations of complex surfaces in the model, and facilitate the more precise acquisition of feature parameters. The related functions studied in the paper will help to further improve the development capability of 3D models based on Open CASCADE, which can make the faster implementation of high-precision simulation design requirements.

Citation Download Citation

Mingxia Zhao "Study on model simulation design based on open CASCADE platform", Proc. SPIE 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021), 1215814 (2 March 2022); https://doi.org/10.1117/12.2627076

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