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激光沉积制造特征分区定义及识别方法研究
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国家重点研发计划项目(2022YFE0122600)、国家自然科学(51975387),


Research on feature islands and identification of method laser deposition manufacturing
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    摘要:

    激光沉积制造技术在飞机框、梁类大型件增材制造方面具有独特的优势,然而应力和变形成为阻碍该技术应用的瓶颈。因此分区工艺被广泛采用以离散制件的残余应力和缓解零件变形。然而,传统分区工艺不考虑零件的几何结构特征易导致不规则的分区搭接,从而引入气孔、熔合不良等缺陷。为了解决这一问题,提出了一种特征分区方法,根据典型框、梁结构件的片层结构几何形状特点,将特征分为“十”字形、T字形、L形和“一”字形四类,并对各类分区特征从形状、姿态和尺寸三方面进行限定,完成分区特征定义。提出一种基于区域骨架线检测的特征识别算法,利用骨架化算法有效简化特征并保留构型特性,采用向量叉乘法、定比分点法对特征区域骨架线完成特征角、平面姿态角及特征分支数等相关参数计算。通过比较计算值和定义值实现特征类型识别。采用典型飞机框件模型的切片数据对算法进行了验证,结果表明该算法能够快速而准确地识别各类特征,实现零件自动特征分区,为智能化增材制造技术打下基础。

    Abstract:

    Laser deposition manufacturing (LDM) technology has unique advantages in additive manufacturing of large aircraft frames and beams. However, stress and deformation have become bottlenecks that hinder the application of this technology. Therefore, the islands process is widely used to discrete the residual stress and alleviate the deformation of the parts. However, the traditional islands process does not take into account the geometric structural features of parts easily lead to irregular partition lap, which introduced pores, poor fusion and other defects. In order to solve this problem, a feature islands method is proposed. According to the geometric shape characteristics of the slicing layers of typical frame and beam structural parts, The features are classified into four types: “十”-shape, T-shape, L-shape and “一”-shape features, and all kinds of features are limited from three aspects :shape, pose and size to complete the definition of island features. A feature recognition algorithm based on region skeleton line detection is proposed, where the skeletonization is used to effectively simplify the features and retain the part characteristics. The vector cross-product and fixed-ratio point method are used to calculate the relevant parameters such as feature angle, plane attitude angle and number of feature branches. Feature type identification is achieved by comparing calculated values with defined values. The algorithm is verified by slice data of a typical aircraft frame model. The results show that the algorithm can quickly and accurately identify various features to realize automatic feature islands of parts, which lays a foundation for intelligent additive manufacturing technology.

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钦兰云,张晶晶,王伟,杨光.激光沉积制造特征分区定义及识别方法研究[J].稀有金属材料与工程,2024,53(1):148~158.[Qin Lanyun, Zhang Jingjing, Wang Wei, Yang Guang. Research on feature islands and identification of method laser deposition manufacturing[J]. Rare Metal Materials and Engineering,2024,53(1):148~158.]
DOI:10.12442/j. issn.1002-185X.20220964

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历史
  • 收稿日期:2022-12-12
  • 最后修改日期:2023-03-01
  • 录用日期:2023-03-07
  • 在线发布日期: 2024-01-29
  • 出版日期: 2024-01-24