Reverse engineering of additive manufactured composite part by toolpath reconstruction using imaging and machine learning

Reverse engineering of additive manufactured composite part by toolpath reconstruction using imaging and machine learning
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使用成像和机器学习通过刀具路径重建对增材制造复合材料零件进行逆向工程

DOI:
10.1016/j.compscitech.2020.108318
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发表时间:
2020
影响因子:
9.1
通讯作者:
Gupta, Nikhil
Gupta, Nikhil
中科院分区:
材料科学1区
文献类型:
--
作者:
Yanamandra, Kaushik;Chen, Guan Lin;Xu, Xianbo;Mac, Gary;Gupta, Nikhil

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复合材料零件的开发需要大量的研究和开发工作。纤维的尺寸、体积分数和方向是决定零件性能的重要因素。添加剂制造(AM)方法越来越多地用于印刷复合材料。3D扫描和成像技术的进步在AM制造的零件的逆向工程中引起了极大的关注,这可能导致假冒和未经授权生产高质量的零件。本文主要研究了利用成像方法和机器学习技术对复合材料零件进行逆向工程,利用微观结构的机器学习技术实现三维打印过程中的几何信息获取和刀具路径重构。对于逆向工程模型,尺寸精度仅相差0.33%。
Development of composite material parts requires significant research and development effort. The fiber size, volume fraction and direction are important in determining the properties of the part. Additive manufacturing (AM) methods are increasingly used for printing composite materials. Advancements in 3D scanning and imaging technology have raised a significant concern in reverse engineering of parts made by AM, which may result in counterfeiting and unauthorized production of high quality parts. This work is focused on using imaging methods and machine learning to reverse engineer a composite material part, where not only the geometry is captured but also the tool path of 3D printing is reconstructed using machine learning of microstructure. A dimensional accuracy with only 0.33% difference is achieved for the reverse engineered model.
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