Characterisation of freeform, structured surfaces in T-spline spaces and its applications
Characterisation of freeform, structured surfaces in T-spline spaces and its applications
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T 样条空间中自由形状结构化表面的表征及其应用
DOI：
10.1088/2051-672x/abf408
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发表时间：
2021-06-01
影响因子：
2.7
通讯作者：
Jiang, Xiangqian Jane
中科院分区：
文献类型：
--
作者：
Wang, Jian;Zou, Renqi;Jiang, Xiangqian Jane
在先进制造中，具有确定性自由形式和嵌入式结构的表面形貌设计已被证明包含有效的附加功能。这些表面需要根据设计的形式和结构进行几何特征描述。然而，这是有问题的，因为现有的表征技术，如多项式形式去除，高斯/样条/小波滤波，基于场的统计参数化，光谱和分形分析不提供令人满意的结果。因此，本文提出了一种有效的T样条拟合算法，将复杂曲面拟合到T样条空间，即基样条空间沿着有T形连接的空间中。几个案例研究表明，所提出的方法是兼容的，并具有显着的潜力，具有挑战性的特征化任务，包括非欧几里德自由形式的删除，边缘保留过滤与多尺度分析，分散的数据插值和平滑，智能大数据下采样或压缩。
In advanced manufacturing, surface topographical designs with deterministic freeform and embedded structures have proven to contain effective, additive functionalities. These surfaces need to be geometrically characterised regarding the designed form and structures. However, this is problematic since existing characterisation techniques such as polynomial form removal, Gaussian/spline/wavelet filtration, field-based statistical parameterisation, spectral and fractal analysis do not provide satisfying results. In this paper, we, therefore, propose to characterise the complex surfaces in T-spline spaces, i.e. basis spline spaces along with T-junctions, using an efficient T-spline fitting algorithm. Several case studies show that the proposed method is compatible and has notable potentials for the challenging characterisation tasks, including non-Euclidean freeform removal, edge-reserving filtration with multiscale analysis, scattered data interpolation and smoothing, and smart large-data downsampling or compression.