Deformation Reconstruction of Injection Molded Part Based on Stratified ICP Registration and B-spline Fitting

Junhao Ouyang, Z. Qiu, Sinan Yuan
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Abstract

Injection molding is a multi-field interacted process with high pressure, high speed and high temperature, which leads to that the deformation and its microcosmic distribution of molded part are intractable to measure and describe accurately. In this paper, a deformation reconstruction method based on the stratified Iterative Closed Point (ICP) registration and B-spline fitting was proposed. In the method, an adaptive smoothing filtering algorithm was presented to process the measured point cloud, and the registration considering the impact of the deformation was applied to align the measured to the ideal point clouds to get accurate deformation, and the cubic B-spline surface interpolation algorithm was utilized for the deformation reconstruction. The experiment results showed that the developed adaptive filtering could better smooth the data than the traditional mean, median, and Gaussian filtering algorithms, and the error of the stratified ICP was about 13% less than that of the traditional ICP and the transformation reliabilities were improved, furthermore, the deformation values, corresponding positions, and microcosmic distribution of deformation were completely supplemented.
基于分层ICP配准和b样条拟合的注塑件变形重建
注射成型是一个高压、高速、高温的多场相互作用的过程,这导致成型件的变形及其微观分布难以准确测量和描述。提出了一种基于分层迭代闭点配准和b样条拟合的变形重建方法。该方法采用自适应平滑滤波算法对测量点云进行处理,采用考虑变形影响的配准方法将测量点云与理想点云对齐,获得精确变形,采用三次b样条曲面插值算法进行变形重建。实验结果表明,所开发的自适应滤波比传统的均值、中值和高斯滤波算法能更好地平滑数据,分层ICP的误差比传统ICP的误差小13%左右,提高了变换的可靠性,并完整地补充了变形值、对应位置和变形的微观分布。
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