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Experimental study of non-measured points on surface measurement using structured illumination microscopy

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Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Non-measured points (NMPs) are one of vital problems in optical measurement. The number and location of NMPs affect the obtained surface texture parameters. Therefore, systematic studying of the NMP is meaningful in understanding the instrument performance and optimizing measurement strategies. This paper investigates the influence of measurement settings on the non-measured points ratio (NMPR) using structured illumination microscopy. It is found that using a low magnification lens, high exposure time, high dynamic range (HDR) lighting levels, and low vertical scanning interval may help reduce the NMPR. In addition, an improved approach is proposed to analyze the influence of NMP on areal surface texture parameters. The analysis indicates that the influence of NMP on some parameters cannot be ignored, especially for extreme height parameters and feature parameters.
Rocznik
Strony
763--778
Opis fizyczny
Bibliogr. 24 poz., rys., tab., wykr., wzory
Twórcy
autor
  • Chemnitz University of Technology, Department of Production Measuring Technology, Reichenhainer Straße 70, 09126 Chemnitz, Germany
  • Chemnitz University of Technology, Department of Production Measuring Technology, Reichenhainer Straße 70, 09126 Chemnitz, Germany
Bibliografia
  • [1] Leach, R. (Ed.). (2013). Characterisation of Areal Surface Texture. Springer Science & Business Media.
  • [2] International Organization for Standardization. (1997). Geometrical Product Specifications (GPS) - Surface texture: Profile method - Terms, definitions and surface texture parameters (ISO 4287:1997). https://www.iso.org/standard/10132.html
  • [3] International Organization for Standardization. (2012). Geometrical product specifications (GPS) - Surface texture: Areal - Part 2: Terms, definitions and surface texture parameters (ISO 25178-2:2012). https://www.iso.org/standard/42785.html
  • [4] Todhunter, L. D., Leach, R. K., Lawes, S. D., & Blateyron, F. (2017). Industrial survey of ISO surface texture parameters. CIRP Journal of Manufacturing Science and Technology, 19, 84-92. https://doi.org/10.1016/j.cirpj.2017.06.001
  • [5] International Organization for Standardization. (2020). Geometrical product specifications (GPS) - Surface texture: Areal - Part 700: Calibration, adjustment and verification of areal topography measuring instruments (ISO/DIS 25178-700:2020).
  • [6] Leach, R. (Ed.). (2011). Optical Measurement of Surface Topography (Vol. 8). Springer Berlin Heidelberg.
  • [7] Miller, T., Adamczak, S., Świderski, J., Wieczorowski, M., Łętocha, A., & Gapiński, B. (2017). Influence of temperature gradient on surface texture measurements with the use of profilometry. Bulletin of the Polish Academy of Sciences. Technical Sciences, 65(1). https://doi.org/10.1515/bpasts-2017-0007
  • [8] Grochalski, K., Wieczorowski, M., Pawlus, P., & H’Roura, J. (2020). Thermal sources of errors in surface texture imaging. Materials, 13(10), 2337. https://doi.org/10.3390/ma13102337
  • [9] He, B., Ding, S., Wei, C., & Shi, Z. (2021). The Influence of the Choice of a Gaussian Filter on the Determination of Areal Surface Texture Parameters. Instruments and Experimental Techniques, 64(1), 71-77. https://doi.org/10.1134/S0020441220060160
  • [10] He, B., Zheng, H., Ding, S., Yang, R., & Shi, Z. (2021). A review of digital filtering in surface roughness evaluation. Metrology and Measurement Systems, 28(2). https://doi.org/10.24425/mms.2021.136606
  • [11] Podulka, P. (2020). Proposal of frequency-based decomposition approach for minimization of errors in surface texture parameter calculation. Surface and Interface Analysis, 52(12), 882-889. https://doi.org/10.1002/sia.6840
  • [12] Pawlus, P., Reizer, R., & Wieczorowski, M. (2017). Problem of non-measured points in surface texture measurements. Metrology and Measurement Systems, 24(3), 525-536. https://doi.org/10.1515/mms-2017-0046
  • [13] Wang, C., D’Amato, R., & Gómez, E. (2019). Confidence Distance Matrix for outlier identification: A new method to improve the characterizations of surfaces measured by confocal microscopy. Measurement, 137, 484-500. https://doi.org/10.1016/j.measurement.2019.01.043
  • [14] Leach, R. K., Brown, L., Jiang, X., Blunt, R., Conroy, M., & Mauger, D. (2008). Guide to the measurement of smooth surface topography using coherence scanning interferometry. http://eprintspublications.npl.co.uk/id/eprint/4099
  • [15] Rachakonda, P., Muralikrishnan, B., & Sawyer, D. (2019, May). Sources of errors in structured light 3D scanners. In Dimensional Optical Metrology and Inspection for Practical Applications VIII (Vol. 10991, p. 1099106). International Society for Optics and Photonics. https://doi.org/10.1117/12.2518126
  • [16] Newton, L., Senin, N., Gomez, C., Danzl, R., Helmli, F., Blunt, L., & Leach, R. (2019). Areal topography measurement of metal additive surfaces using focus variation microscopy. Additive Manufacturing, 25, 365-389. https://doi.org/10.1016/j.addma.2018.11.013
  • [17] Feng, X., Senin, N., Su, R., Ramasamy, S., & Leach, R. (2019). Optical measurement of surface topographies with transparent coatings. Optics and Lasers in Engineering, 121, 261-270. https://doi.org/10.1016/j.optlaseng.2019.04.018
  • [18] Gomez, C., Su, R., Thompson, A., DiSciacca, J., Lawes, S., & Leach, R. K. (2017). Optimization of surface measurement for metal additive manufacturing using coherence scanning interferometry. Optical Engineering, 56(11), 111714. https://doi.org/10.1117/1.OE.56.11.111714
  • [19] Li, Z., & Gröger, S. (2021). Investigation of noise in surface topography measurement using structured illumination microscopy. Metrology and Measurement Systems, 28(4). https://doi.org/10.24425/mms.2021.137706
  • [20] Liu, W., Chen, X., Zeng, W., Sun, W., Jiang, X., Scott, P., & Lou, S. (2021, September). FVM and XCT Measurement of Surface Texture of Additively Manufactured Parts. In 2021 26th International Conference on Automation and Computing (ICAC) (pp. 1-6). IEEE. https://doi.org/10.23919/ICAC50006.2021.9594146
  • [21] Bermudez, C., Matilla, A., & Aguerri, A. (2017). Confocal fusion: Towards the universal optical 3D metrology technology. Proceedings of the 12th LAMDAMAP, Renishaw Innovation Center, Wotton-Under-Edge, UK, 15-16. http://www.euspen.eu/knowledge-base/LAM138.pdf
  • [22] Kapłonek, W., Nadolny, K., & Królczyk, G. M. (2016). The use of focus-variation microscopy for the assessment of active surfaces of a new generation of coated abrasive tools. Measurement Science Review, 16(2), 42-53. https://doi.org/10.1515/msr-2016-0007
  • [23] Flys, O., Berglund, J., & Rosén, B. G. (2020). Using confocal fusion for measurement of metal AM surface texture. Surface Topography. Metrology and Properties, 8(2), 024003. https://doi.org/10.1088/2051-672X/ab84c3
  • [24] Confovis GmbH. (n.d.). Structured Illumination Microscopy. Retrieved September 18, 2022. https://www.confovis.com/en/optical-measurement
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2486db5c-f01c-45eb-80e2-093d45e7612c
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