Characterisation of surfaces and coatings

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Review papers

Subject Index

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De Chiffre et al [1] have reviewed the methods used to quantitatively characterise surface texture.  They consider conventional 2D/3D roughness parameters with emphasis on recent international standards and developments.  They present new texture characterisation methods, including fractals, wavelets and change trees, with the respective parameters and applications.

Reflectance Transformation Imaging (RTI) [2, 3] involves taking multiple high-resolution images with light originating from different sources over a series of exposures. The system is a suite of technologies and procedures using photometric stereo to generate an amalgamation of the surface reflectance information. In a joint project between the universities at Southampton and Oxford, the technique was used to enhance features of cultural/historical artefacts.

Fractal dimension.  In conventional notation, a point has dimension 0, a line has dimension 1, an area has dimension 2 and a volume has dimension 3. If a square is decomposed into four (2 x 2 = 2²) self-similar smaller squares then it has magnification 2, and if decomposed into nine (3 x 3 = 3²) smaller squares, it has magnification 3. The dimension is simply the exponent of the number of self-similar pieces into which the figure has been decomposed [4]. The total number of objects, N, is a function of the magnification factor, r, and the dimension, D, as given by N = r^D.  The fractal dimension, D, measures the complexity of a self-similar object.

Labrosse et al [5] proposed a novel procedure for the assessment of the surface finish of in-mould gel-coated fibre-reinforced polymer matrix composites. The technique involves photographing the reflection from a coated surface on an opaque screen and analysing the image using fractal dimensions.  The ranking of the quality of surface finish from this technique sensibly aligned with that obtained by human observation and by the commercial Wavescan DOI system.  The investment required for the new system was primarily a high-resolution digital camera, and hence was below 5% of the cost of the commercial instrument.

Wavelet Texture Analysis (WTA). Palmer et al [6] reanalysed the plates considered by Labrosse et al [5] using the WTA on the digital images to derive an instrumental measure of surface finish quality.  The rank correlation between the human expert surface finish quality ratings and those from the WTA image analysis process was found to be positive, large and statistically significant.  WTA could form the basis of an inexpensive and practical instrumental method for the ranking of fibre-reinforced composite surface finish quality.

Non-destructive measurement of coating thickness.
Sargent [7] used a small, purpose-designed thermal wave system to make non-contact measurements of primer layer thickness on grit-blasted steel surfaces.  The surface phase of a thermal wave (generated using a modulated semiconducting laser) was measured relative to the phase of a laser heating source.  The method had an intrinsic accuracy of ∼±0.1 μm and an absolute accuracy that was limited to ∼±2 μm because of the uncertainty in the paint thermal conductivity.  Thermal wave measurements of thickness agreed with those obtained using an independent contact measurement device within the experimental errors. The variation in accuracy was estimated as a result of stand-off error, integration time and power levels.

Ostiguy et al [8] compared commercial solutions for coating thickness measurement (Table 1).  They also used time-of-flight measurements of low frequency (500 kHz) S₀ ultrasonic guided waves to estimate primer/coating thickness on aluminium plate, or unidirectional carbon fibre epoxy composite with an integrated metalic mesh, substrates.  The technique is insensitive to surface periodicity or roughness.  Experimental precision was <10 μm.

References

1. L De Chiffre, P Lonardo, H Trumpold, DA Lucca, G Goch, CA Brown, J Raja and HN Hansen, Quantitative characterisation of surface texture, CIRP Annals, 2000, 49(2), 635-642, 644-652.
2. G Earl, P Basford, A Bischoff, A Bowman, C Crowther, J Dahl, M Hodgson, L Isaksen, E Kotoula, K Martinez, H Pagi and KE Piquette, Reflectance Transformation Imaging Systems for Ancient Documentary Artefacts, Electronic Visualisation and the Arts (EVA 2011), London, 06-08 July 2011.
3. KE Piquette, Reflectance transformation imaging (RTI) and ancient egyptian material culture, Damqatum : The CEHAO newsletter – El boletín de noticias del CEHAO, Centro de Estudios de Historia del Antiguo Oriente, 2011, 7, 15-20.
4. J Summerscales, Fibre distribution and the process-property dilemma, Chapter 11 in PWR Beaumont and C Soutis (editors): The Structural Integrity of Carbon Fibre Composites: Fifty Years of Progress and Achievement, Springer, 2016, 301-317. ISBN 978-3-319-46120-5.
5. Q Labrosse, CP Hoppins and J Summerscales, Objective assessment of the surface quality of coated surfaces, Insight, January 2011, 53(1), 16-20.
6. S Palmer, W Hall and J Summerscales, Ranking of fibre-reinforced composite plate surface finish quality by wavelet texture analysis, Insight, June 2016, 58(6), 318-323.
7. JP Sargent, Thermal wave thickness measurement of primer on grit-blasted steel, Insight, October 2012, 54(10), 557-561.
8. P-C Ostiguy, N Quaegebeur and P Masson, Non-destructive evaluation of coating thickness using guided waves, NDT & E International, December 2015, 76, 17-25.
9. QNix^® 4500: The global bestseller for standard applications, Automation dr Nix GmbH & Co KG, Cologne ~ Germany, 2014.
10. Product overview: innovative, top quality measurement technology, Fischer Technical report 992-019, Sindelfingen ~ Germany, February 2016.
11. Ultrasonic paint thickness measurement - plastic substrates, Defelsko Inspection Instruments, Ogdensburg NY, 2017.