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面向自动修补的复杂零件孔洞识别

王春香 周国勇 王耀

王春香,周国勇,王耀. 面向自动修补的复杂零件孔洞识别[J]. 机械科学与技术,2021,40(2):257-261 doi: 10.13433/j.cnki.1003-8728.20200056
引用本文: 王春香,周国勇,王耀. 面向自动修补的复杂零件孔洞识别[J]. 机械科学与技术,2021,40(2):257-261 doi: 10.13433/j.cnki.1003-8728.20200056
WANG Chunxiang, ZHOU Guoyong, WANG Yao. Hole Identification of Complex Parts for Automatic Repair[J]. Mechanical Science and Technology for Aerospace Engineering, 2021, 40(2): 257-261. doi: 10.13433/j.cnki.1003-8728.20200056
Citation: WANG Chunxiang, ZHOU Guoyong, WANG Yao. Hole Identification of Complex Parts for Automatic Repair[J]. Mechanical Science and Technology for Aerospace Engineering, 2021, 40(2): 257-261. doi: 10.13433/j.cnki.1003-8728.20200056

面向自动修补的复杂零件孔洞识别

doi: 10.13433/j.cnki.1003-8728.20200056
基金项目: 内蒙古自治区自然科学基金项目(2017MS(LH)0530)与包头市科技计划项目(2019Z3004-6)
详细信息
    作者简介:

    王春香(1962−),教授,硕士生导师,研究方向为逆向工程技术、快速成型技术,wcxcxw@126.com

  • 中图分类号: TP391

Hole Identification of Complex Parts for Automatic Repair

  • 摘要: 依据样点的邻域在其局部微切平面投影的分布情况,提出了一种针对采样密度不均、几何形状复杂、孔洞面积大小不一的散乱点云模型的孔洞识别方法。通过使用NP邻域,使得位于密度过渡区域的点被准确分类;由于样点的邻域可能跨过多个面,常规PCA方法估算的点云法矢不准确,从而导致模型尖锐位置上的点误判,通过引入距离权重,保证了局部微切平面计算的准确性;针对邻域点数k取值较少,检测结果中存在较多噪声点,而k值较大又会覆盖模型中较小的孔洞,通过邻域支持的方法,有效地检测出模型中的小面积孔洞;为有利于自动化修补孔洞,文中采用划分空间栅格聚类的方法确定孔洞位置及数量,避免了点与点之间距离的反复计算,加快了聚类速度。实验结果表明,该方法能有效检测模型中面积大小不一的孔洞,得到的检测结果噪声点少,孔洞轮廓清晰。
  • 图  1  邻域选取

    图  2  内部点与边界点邻域分布

    图  3  邻域点投影及角度逆时针排序

    图  4  孔洞识别结果比较(实验一)

    图  5  不同$k$值的识别结果比较(实验二)

    图  6  孔洞聚类算法的输出结果

    表  1  检测结果与运行时间对比($k = 20$$s = 3$)

    算法检测结果误判点数误判比率/%运行时间/s
    $N_P^k$邻域 11 914 11 532 96.79 1.74
    ${N_P}$邻域 2 541 2 153 84.73 17.61
    本文方法 444 61 13.74 18.03
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-09-29
  • 刊出日期:  2021-02-02

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