Lewis Newton
Comparison and validation of surface topography segmentation methods for feature-based characterisation of metal powder bed fusion surfaces
Newton, Lewis; Senin, Nicola; Smith, Bethan; Chatzivagiannis, Evangelos; Leach, Richard
Authors
Nicola Senin
Bethan Smith
Evangelos Chatzivagiannis
Professor RICHARD LEACH RICHARD.LEACH@NOTTINGHAM.AC.UK
CHAIR IN METROLOGY
Abstract
Feature-based characterisation, i.e. the characterisation of surface topography based on the isolation of relevant topographic formations (features) and their dimensional assessment, is a developing field of surface texture metrology. Feature-based approaches provide dimensional assessments of individual features (area, width, height, etc.) as well as statistical properties of feature aggregations (e.g. mean, standard deviation, etc.), which may be more intuitive or related to functionality. For powder bed fusion surfaces, a commonly investigated feature of interest is the particles or spatter present on the surface. In this work, we address segmentation, a necessary step of feature-based characterisation, where the measured surface topography is spatially partitioned into regions to isolate the targeted features from their surroundings. Three topography segmentation methods are investigated: morphological segmentation on edges, contour stability analysis and active contours. To perform the comparison, three powder bed fusion surfaces obtained at differing build orientations (0°, 30° and 90°) and measured using focus variation microscopy are subjected to the three segmentation approaches-optimised to isolate spatter and particles on the surface. The comparison of the segmentation methods focuses on performance in feature identification (i.e. the capability to correctly detect the presence of features) and performance in feature boundary determination (i.e. the capability to correctly trace the boundaries of each feature). Results show that no segmentation method is consistently superior for all test cases, but the comparison approach is useful to explore and optimise segmentation alternatives for feature-based characterisation scenarios.
Citation
Newton, L., Senin, N., Smith, B., Chatzivagiannis, E., & Leach, R. (2019). Comparison and validation of surface topography segmentation methods for feature-based characterisation of metal powder bed fusion surfaces. Surface Topography: Metrology and Properties, 7(4), Article 045020. https://doi.org/10.1088/2051-672X/ab520a
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 28, 2019 |
Online Publication Date | Nov 7, 2019 |
Publication Date | Nov 7, 2019 |
Deposit Date | Oct 25, 2019 |
Publicly Available Date | Oct 25, 2019 |
Journal | Surface Topography: Metrology and Properties |
Electronic ISSN | 2051-672X |
Publisher | IOP Publishing |
Peer Reviewed | Peer Reviewed |
Volume | 7 |
Issue | 4 |
Article Number | 045020 |
DOI | https://doi.org/10.1088/2051-672X/ab520a |
Keywords | areal surface topography, surface texture, feature-based characterisation, additive manufacturing |
Public URL | https://nottingham-repository.worktribe.com/output/2965659 |
Publisher URL | https://iopscience.iop.org/article/10.1088/2051-672X/ab520a/meta |
Contract Date | Oct 25, 2019 |
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Comparison and validation of surface topography segmentation methods for feature-based characterisation of metal powder bed fusion surfaces
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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