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基于曲率匹配和递归排序的自适应排样算法

Adaptive Nesting Algorithm Based on Curvature Matching and Recursive Sorting

  • 摘要: 为提高盘状毛坯的使用率,提出一种口腔修复加工中模型边界在盘状毛坯中的排样算法,主要包括边界匹配、多边形定位及递归排序.首先基于协方差矩阵及矩阵SVD分解算法对模型多边形进行分段,并采用等弧长曲线采样曲率匹配确定待匹配模型边界;然后依毛坯边界角度分布及沿圆周排样的思想确定模型轮廓的旋转和平移定位;最后提出一种基于包络率的递归排序算法,对在排样过程中发现的大孔洞可动态地调整排样顺序.实验结果表明,该算法可以处理不规则模型边界在任意形状毛坯中的排样,能有效地降低加工成本.

     

    Abstract: In order to improve utilization of disc blank,an adaptive nesting algorithm of dental restoration models was proposed.Polygon was segmented accurately by covariance matrix and SVD decomposition.The border to be matched on model was calculated by equal arc-length sampling and curvature matching in single model nesting.Rotation and translation was determined by angular distribution of blank.The recursive sorting algorithm based on rate of enclosure was proposed.It can adjust the sequence dynamically when big holes were found.Experimental results show that the algorithm can deal with nesting of irregular boundary on arbitrary-shape blank and has great utility value.

     

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