期刊
MEASUREMENT
卷 186, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2021.110207
关键词
Additive manufacturing; Classification; Point cloud; Quality inspection; 2D Fourier transform
This research establishes a framework to quantify the similarity of 3D surface topography measurements and determine whether they are from the same surface in the frequency domain after 2D Fourier transformation. It provides a new perspective for surface topography similarity evaluation and serves as a benchmark work in 3D surface topography feature extraction. The work has the potential to benefit quality assurance in additive manufacturing and other fields where surface topography data is valuable.
3D surface topography provides critical information about surface textures and has begun to be used in additive manufacturing applications such as in-situ 3D monitoring and sample porosity comparisons, etc. In this research, we establish a thorough framework to quantify the similarity of 3D surface topography measurements and determine whether they are from the same surface or not based on the frequency domain representations after 2D Fourier transformation. Two measurements portraying the same surface are defined as a matched pair while the others are unmatched. This framework quantifies the similarity effectively, provides a new perspective for surface topography similarity evaluation, and serves as a benchmark work in 3D surface topography feature extraction in the frequency domain. Our work has a great potential to benefit not only the quality assurance of AM but also many other communities where surface topography data is useful.
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