Three-dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling
Three-dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling
复制标题
拟合算法对集成芯片形貌建模的三维模糊影响分析
DOI：
10.1007/s12206-012-0832-6
复制
发表时间：
2012-10-01
影响因子：
1.6
通讯作者：
Brauwer, Richard Kars
中科院分区：
文献类型：
--
作者：
Liang, Zhongwei;Ye, Bangyan;Brauwer, Richard Kars
在检查不同外部参数条件下表面精度建模的详细性能结果时，应在地形空间建模过程中对集成芯片表面进行评估和评估。曲面拟合算法的应用对地形数学特征产生了相当大的影响。不同表面拟合算法对集成芯片表面造成的影响机制，有利于不同外部参数条件的定量分析。通过从选定的物理控制点中提取坐标信息，并使用一套精密的空间坐标测量设备，利用几种典型的曲面拟合算法，利用获得的点云构建微地形模型。在计算新提出的表面模型数学特征时，我们构造了模糊评价数据序列，并提出了一种新的三维模糊定量评价方法。通过该方法，可以清晰地量化地形特征的值变化趋势。可以定量、详细地分析不同曲面拟合算法、地形空间特征以及外部科学参数条件之间的模糊影响规律。此外，定量分析可以对不同表面拟合算法性能结果的内在影响机制和内部数学关系、表面微建模情况下的地形空间特征及其科学参数条件提供最终结论。表面精度建模的性能检查将作为微表面重建的新研究思路得到促进和优化，并在建模过程中进行监控。
In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface-fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface-fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface-fitting algorithms are used for constructing micro-topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three-dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface-fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface-fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process.