Comparison and validation of surface topography segmentation methods for feature-based characterisation of metal powder bed fusion surfaces

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.

Multi-view fringe projection system for surface topography measurement during metal powder bed fusion

“…Future testing of the system's capabilities will include featurebased segmentation [60][61][62][63] of the multi-view fringe projection measurements to assess how well metal PBF surface features can be identified using this approach. The multi-view system is now being commercialized by Taraz Metrology Ltd. and will be tested in several commercial PBF systems.…”

“…From these publications, fringe projection methods have been demonstrated to have potential for in-process monitoring of AM systems. However, improvements need to be made to achieve a higher-resolution surface reconstruction that can be used for feature-based identification of defects [60][61][62][63] that are sub-100 µm in lateral size. A feature-based identification approach could provide a more robust method of determining the successful manufacture of each additive layer and, therefore, the whole component.…”

Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces

“…impact based surface treatments such as shot peening 2 , 11 ; in addition they neglect spatial information about peaks and valleys. While the standards define other parameters exploiting the spatial information, these rely either on the choice of the evaluation length or area, or -in the case of feature-based characterisation- on appropriate use of segmentation of the surface 12 . Area-based topographical characterization has gathered attention in recent years.…”

Feature-Based Characterisation of Turned Surface Topography with Suppression of High-Frequency Measurement Errors

“…Furthermore, the statistical properties of feature aggregations, such as mean or standard deviation, may be more intuitive or related to functionality and could be assessed with a feature-based characterisation. Moreover, isolating relevant topographic formations, regularly defined as features, is a developing field of study in surface topography measurement [46,47]. Examples of feature characterisation are methods with excluding valleys approaches [48,49].…”