Similarity quantification of 3D surface topography measurements
Similarity quantification of 3D surface topography measurements
Date
2021-12
Authors
Jiang, Yiqun
Wang, Shaodong
Qin, Hantang
Li, Beiwen
Wang, Shaodong
Qin, Hantang
Li, Beiwen
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Altmetrics
Authors
Research Projects
Organizational Units
Industrial and Manufacturing Systems Engineering
Organizational Unit
Journal Issue
Series
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.
Description
Keywords
Additive manufacturing,
Classification,
Point cloud,
Quality inspection,
2D Fourier transform