Dimensional metrology of micro parts by optical three-dimensional profilometry and areal surface topography analysis

Senin, Nicola; Blunt, Liam; Tolley, M.

doi:10.1177/0954405412461240

Cited by 15 publications

(10 citation statements)

References 14 publications

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“…The first route aims at computing dimensional and geometric attributes from measured topography, so that a one-to-one mapping with design specifications is achieved (thus allowing for direct verification akin to common practice in dimensional metrology for standard-sized mechanical parts). Examples of this approach can be found in previous publications [17], [18], and have been specifically applied to tessellated surfaces [19]. The second characterisation route, which is the subject of this paper, is about computing shape descriptors; that is, fast transforms turning topography data into a finite series of numbers useful for shape encoding.…”

Section: Metrological Characterisation Of Tessellated Surfacesmentioning

confidence: 99%

Shape descriptors and statistical classification on areal topography data for tile inspection in tessellated surfaces

2017

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Verification of conformance to design specifications in production, and identification of defects related to wear or other damage during maintenance, are key metrological aspects that must be addressed for micro-scale tessellated surfaces. A new algorithmic approach is presented that operates on topography datasets as obtained by areal topography instruments. The approach combines segmentation algorithms with a novel implementation of the angular radial transform, originally adopted by the MPEG-7 standard, to implement shape descriptors and associated similarity metrics. Applications to the inspection and verification of laser-manufactured micro-embossing topographies are illustrated. The topographies are first segmented to extract the individual tiles; the tiles are then encoded through shape descriptors. Principal component analysis and cluster analysis are used to investigate the behaviour of the angular radial transform coefficients. Finally, an algorithmic classifier based on supervised learning (k-nearest neighbours) is implemented and shown to be effective at identifying defects and at discriminating between defect types.

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Section: Metrological Characterisation Of Tessellated Surfacesmentioning

confidence: 99%

Shape descriptors and statistical classification on areal topography data for tile inspection in tessellated surfaces

2017

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“…For the fusion of point clouds, levelling rotation [74] is an optional step before registration. The coordinate system of a dataset is rotated so that the surface points lie approximately horizontally.…”

Section: Pre-processes 1) Levelling Rotationmentioning

confidence: 99%

Review of the mathematical foundations of data fusion techniques in surface metrology

Wang

Leach

Jiang

2015

Surf. Topogr.: Metrol. Prop.

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The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed.

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“…However, adapting data analysis and processing algorithms so that they can discriminate between valid and non-valid points (e.g. through masking solutions) is generally not straightforward and speed/time performance may suffer [9,10]. Therefore, correction of non-measured points is often a simpler solution.…”

Section: Treatment Of Non-measured Pointsmentioning

confidence: 99%

Review of feature boundary identification techniques for the characterization of tessellated surfaces

MacAulay

Senin

Giusca

et al. 2015

Surf. Topogr.: Metrol. Prop.

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Tessellated surfaces are structured surfaces where the dominant features are organised in periodic patterns. Tessellated surfaces are becoming increasingly popular for a wide variety of industrial uses. However, their uptake is hindered by a lack of suitable metrological techniques to categorise and verify their properties. Areal surface texture parameters, commonly used for characterisation of surface texture, may not provide relevant information for characterising the periodicity and the other functionally relevant geometric attributes of the pattern. A possible solution, recently proposed in the literature, is to directly retrieve the individual features of the pattern and to determine their relevant geometric and dimensional properties. To achieve such a characterisation it is necessary to segment the surface in order to extract the pattern units (tiles) and the individual features contained within, so that their properties can be assessed. This paper reviews a number of different techniques and compares their ability to accurately identify the tile features and their boundaries. This ability is important as it has a direct impact on the computation of dimensional and geometric properties of the features.

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Dimensional metrology of micro parts by optical three-dimensional profilometry and areal surface topography analysis

Cited by 15 publications

References 14 publications

Shape descriptors and statistical classification on areal topography data for tile inspection in tessellated surfaces

Shape descriptors and statistical classification on areal topography data for tile inspection in tessellated surfaces

Review of the mathematical foundations of data fusion techniques in surface metrology

Review of feature boundary identification techniques for the characterization of tessellated surfaces

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