Similarity quantification of 3D surface topography measurements

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Date

2021-12

Authors

Jiang, Yiqun
Wang, Shaodong
Qin, Hantang
Li, Beiwen

Publisher

Elsevier

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Organizational Units

Industrial and Manufacturing Systems Engineering

Organizational Unit

Department

Industrial and Manufacturing Systems Engineering

Abstract

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.

Comments

This is a manuscript of an article published as Jiang, Yiqun, Shaodong Wang, Hantang Qin, Beiwen Li, and Qing Li. "Similarity quantification of 3D surface topography measurements." Measurement 186 (2021): 110207. DOI: 10.1016/j.measurement.2021.110207. Copyright 2021 Elsevier Ltd. Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). Posted with permission.

Keywords

Additive manufacturing, Classification, Point cloud, Quality inspection, 2D Fourier transform