基于部分先验识别的B-Rep模型全局对称性识别方法
发布时间：2019-06-05 11:58
【摘要】：B-Rep模型对称性识别能有效地提高CAE分析效率.针对现有方法通过识别B-Rep模型所有局部对称性来确定全局对称性,效率较低的问题,提出一种基于部分先验识别的B-Rep模型全局对称性识别方法.该方法以一致面集为对称性识别单元,首先利用先验知识快速确定部分局部对称性,然后通过几何推理逐步缩小候选对称性识别范围,最终快速确定B-Rep模型全局对称性.实验结果证明,文中方法鲁棒性高且识别速度快.
[Abstract]:Symmetry recognition of B-Rep model can effectively improve the efficiency of CAE analysis. In order to solve the problem that the existing methods determine the global symmetry by identifying all the local symmetries of B-Rep model, a global symmetry recognition method of B-Rep model based on partial priori recognition is proposed. In this method, the uniform surface set is used as the symmetry recognition unit. Firstly, the partial local symmetry is determined quickly by using prior knowledge, and then the candidate symmetry recognition range is gradually reduced by geometric reasoning, and finally the global symmetry of B-Rep model is determined quickly. The experimental results show that the proposed method has high robustness and fast recognition speed.
【作者单位】： 河海大学物联网工程学院;常州市图形图像与骨科植入物数字化技术重点实验室;
【基金】：国家自然科学基金青年项目(61403120);国家自然科学基金面上项目(61472118) 江苏省科技支撑计划(BE2014048)
【分类号】：TP391.72
，
本文编号：2493510
[Abstract]:Symmetry recognition of B-Rep model can effectively improve the efficiency of CAE analysis. In order to solve the problem that the existing methods determine the global symmetry by identifying all the local symmetries of B-Rep model, a global symmetry recognition method of B-Rep model based on partial priori recognition is proposed. In this method, the uniform surface set is used as the symmetry recognition unit. Firstly, the partial local symmetry is determined quickly by using prior knowledge, and then the candidate symmetry recognition range is gradually reduced by geometric reasoning, and finally the global symmetry of B-Rep model is determined quickly. The experimental results show that the proposed method has high robustness and fast recognition speed.
【作者单位】： 河海大学物联网工程学院;常州市图形图像与骨科植入物数字化技术重点实验室;
【基金】：国家自然科学基金青年项目(61403120);国家自然科学基金面上项目(61472118) 江苏省科技支撑计划(BE2014048)
【分类号】：TP391.72
，
本文编号：2493510
本文链接：https://www.wllwen.com/kejilunwen/ruanjiangongchenglunwen/2493510.html
