Similarity of Tessellated Solid Models for Engineering Applications
Similarity of Tessellated Solid Models for Engineering Applications
复制标题
工程应用中曲面细分实体模型的相似性
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Christopher Sousa
中科院分区：
文献类型：
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作者：
Rahul Sharan Renu;Christopher Sousa
本研究的目的是探讨一种实体模型相似性评估方法的性能。此方法用于评估镶嵌实体模型的相似性，其中镶嵌几何形状为三角形-具体而言，该方法比较STL文件。为每个被比较的实体模型生成（三角形）镶嵌区域的直方图。两个实体模型直方图的差异表明它们的不同。实体模型相似性评估方法的性能评估通过改变镶嵌分辨率，并通过改变直方图箱大小。实体模型相似性评估方法也比较了文献中的方法。使用来自Engineering Shape Benchmark的867个实体模型进行全面测试。结果发现，该方法是强大的，在其灵敏度直方图箱大小，并在其灵敏度镶嵌分辨率的鲁棒性。结果发现，对于小的检索尺寸，精度相对较高。它还发现，这种方法优于文献中的方法比较模型时，是矩形，扁平，薄，和/或立方体。此外，这种方法的缺点和相关的未来工作进行了识别。
The objective of this research is to investigate the performance of a solid model similarity assessment method. This method is used to assess the similarity of tessellated solid models, where the tessellated geometry is in the form of triangles — specifically, the method compares STL files. A histogram of (triangle) tessellation areas is generated for each solid model being compared. The difference in the histograms of two solid models indicates their dissimilarity. The performance of the solid model similarity assessment method is evaluated by varying tessellation resolutions, and by varying histogram bin sizes. The solid model similarity assessment method is also compared to methods from literature. The comprehensive testing was performed using 867 solid models from the Engineering Shape Benchmark. It is found that the method was robust in its sensitivity to histogram bin sizes, and robust in its sensitivity to tessellation resolution. It is found that for small retrieval sizes, precision is relatively high. It is also found that this method outperformed methods from literature when comparing models that are rectangular, flat, thin, and/or cubic. Additionally, shortcomings of this method and related future work is identified.