1,721,015 research outputs found
“On Three-dimensional Surface Topography Analysis Process Planning and Documenting for Engineering Applications”,
No full textA contribution to the development of three-dimensional nano and micro-topography measurement and analysis techniques and systems
No full textInformation-rich surface metrology
No full textInformation-rich metrology refers to the incorporation of any type of available information in the data acquisition and processing pipeline of a measurement process, in order to improve the efficiency and quality of the measurement. In this work, the information-rich metrology paradigm is explored as it is applied to the measurement and characterisation of surface topography. The advantages and challenges of introducing heterogeneous information sources in the surface characterisation pipeline are illustrated. Examples are provided about the incorporation of structured knowledge about a part nominal geometry, the manufacturing processes with their signature topographic features and set-up parameters, and the measurement instruments with their performance characteristics and behaviour in relation to the specific properties of the surfaces being measured. A wide array of surface metrology applications, ranging from product inspection, to surface classification, to defect identification and to the investigation of advanced manufacturing processes, is used to illustrate the information-rich paradigm
Automated identification and extraction of dale-like features from the three-dimensional topography of manufactured surfaces: an application to scratch testing
No full textBioceramic Materials Surface Topography Measurement and Analysis for Biomedical Applications
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Identification of microtopographic surface features and form error assessment
No full textThis work is concerned with quality inspection of microtopographic surface features, such as those that may be commonly found in semiconductor products, microelectromechanical systems, and other microcomponents. Surface microtopography data are assumed to be available as a height map, acquired through raster scanning over the region of interest, by means of a 3D profilometer or a 3D scanning microscope. An algorithmic procedure is proposed for form error assessment, which comprises several steps: first the feature of interest is localized and identified within the height map; then it is extracted and aligned with a reference (i.e., nominal) geometry modeled by means of a CAD system; finally, form error is evaluated from the volume enclosed between the two aligned geometries. Feature identification is implemented through a modified version of the ring projection transform, adapted to operate on topography height maps; alignment comprises two steps (coarse alignment, consisting in an exhaustive search over discrete angular positions; and fine alignment, done with the iterative closest point technique). The final form error assessment procedure is applied to aligned geometries. The approach is illustrated and validated first through its application to an artificially generated case study, then to a real-life case of industrial relevance. © 2010 Springer-Verlag London
Layer inspection via digital imaging and machine learning for in-process monitoring of fused filament fabrication
No full textWe present a solution for layer inspection based on digital imaging and machine learning (ML) suitable for application to in-process monitoring of fused filament fabrication. Top-down images of the layer are captured in-process via a digital camera, decomposed into patches representing specific types of topographic patterns, and processed through a binary classifier, trained to recognize acceptable and out-of-control states in relation to the presence/absence of topographic defects. Classifiers implementing different types of ML technologies (support vector machines on dense image features, convolutional neural networks of different depths, and convolutional autoencoder) are investigated and compared in terms of performance at detecting layer defects. The generalizability of the approach to different part geometries is also discussed. A prototype implementation is illustrated through application to selected test parts. Research achievements as well as open challenges are highlighted
Quality Inspection of Microtopographic Surface Features with Profilometers and Microscopes
No full textWith the increasingly widespread adoption of micromanufacturing solutions and with the production of a growing number of artifacts defined at the microscopic and submicroscopic scales, increasingly smaller geometries need to be verified for quality assurance. The study of precision at micro and submicro scales is gaining considerable interest: relevant issues pertain to how to define allowable geometric error on parts of such small sizes (e.g., semiconductor products, microelectromechanical systems, other microcomponents) with proper dimensional and geometric tolerances, and how to measure them. This work addresses the specific problem of assessing geometric error associated with micromanufactured surface features. Three-dimensional digital microscopes and profilometers for microtopography analysis are increasingly being adopted for such a task, owing to their suitability to operate at very small scales. However, this raises several challenges, as three-dimensional microscopes and profilometers have traditionally been used in different application domains, and are mainly aimed at the inspection of surface finish; new modes of operation must be identified which take into consideration such peculiarities. Both families of instruments need to be closely investigated, and their main constraints and benefits dissected and analyzed to assess their adaptability to the new task of assessing geometric error on micromanufactured parts or surface features. © 2010 Springer-Verlag London
Assessment of surface topography modifications through feature-based registration of areal topography data
No full textSurface topography modifications due to wear or other factors are usually investigated by visual and microscopic inspection, and-when quantitative assessment is required-through the computation of surface texture parameters. However, the current state-of-The-Art areal topography measuring instruments produce detailed, areal reconstructions of surface topography which, in principle, may allow accurate comparison of the individual topographic formations before and after the modification event. The main obstacle to such an approach is registration, i.e. being able to accurately relocate the two topography datasets (measured before and after modification) in the same coordinate system. The challenge is related to the measurements being performed in independent coordinate systems, and on a surface which, having undergone modifications, may not feature easily-identifiable landmarks suitable for alignment. In this work, an algorithmic registration solution is proposed, based on the automated identification and alignment of matching topographic features. A shape descriptor (adapted from the scale invariant feature transform) is used to identify landmarks. Pairs of matching landmarks are identified by similarity of shape descriptor values. Registration is implemented by resolving the absolute orientation problem to align matched landmarks. The registration method is validated and discussed through application to simulated and real topographies selected as test cases
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