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Investigation of noise in surface topography measurement using structured illumination microscopy

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Noise is a fundamental metrological characteristic of the instrument in surface topography measurement. Therefore, measurement noise should be thoroughly studied in practical measurement to understand instrument performance and optimize measurement strategy. This paper investigates the measurement noise at different measurement settings using structured illumination microscopy. The investigation shows that the measurement noise may scatter significantly among different measurement settings. Eliminating sample tilt, selecting low vertical scanning interval and high exposure time is helpful to reduce the measurement noise. In order to estimate the influence of noise on the measurement, an approach based on metrological characteristics is proposed. The paper provides a practical guide to understanding measurement noise in a wide range of applications.
Rocznik
Strony
767--779
Opis fizyczny
Bibliogr. 36 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] International Organization for Standardization. (2019). Geometrical product specifications (GPS) - Surface texture: Areal - Part 600: Metrological characteristics for areal topography measuring methods (ISO 25178-600:2019). https://www.iso.org/standard/67651.html
  • [2] de Groot, P., & DiSciacca, J. (2020). Definition and evaluation of topography measurement noise inoptical instruments. Optical Engineering, 59(6), 064110. https://doi.org/10.1117/1.OE.59.6.064110
  • [3] Eifler, M., Hering, J., Seewig, J., Leach, R. K., von Freymann, G., Hu, X., & Dai, G. (2020). Comparison of material measures for areal surface topography measuring instrument calibration. Surface Topography: Metrology and Properties, 8(2), 025019. https://doi.org/10.1088/2051-672X/ab92ae
  • [4] Vanrusselt, M., Haitjema, H., Leach, R., & de Groot, P. (2021). International comparison of noise in areal surface topography measurements. Surface Topography: Metrology and Properties, 9(2), 025015. https://doi.org/10.1088/2051-672X/abfa29
  • [5] Giusca, C. L., Leach, R. K., Helary, F., Gutauskas, T., & Nimishakavi, L. (2012). Calibration of the scales of areal surface topography-measuring instruments: Part 1. Measurement noise and residual flatness. Measurement Science and Technology, 23(3), 035008. https://doi.org/10.1088/0957-0233/23/3/035008
  • [6] 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
  • [7] Fu, S., Cheng, F., Tjahjowidodo, T., Zhou, Y., & Butler, D. (2018). A non-contact measuring system for in-situ surface characterization based on laser confocal microscopy. Sensors, 18(8), 2657. https://doi.org/10.3390/s18082657
  • [8] Barker, A., Syam, W. P., & Leach, R. K. (2016, October). Measurement noise of a coherence scanning interferometer in an industrial environment. Proceedings of the Thirty-First Annual Meeting of the American Society for Precision Engineering (vol. 65, pp. 594-599). http://eprints.nottingham.ac.uk/id/eprint/38454
  • [9] Gomez, C., Su, R., De Groot, P., & Leach, R. (2020). Noise reduction in coherence scanning interferometry for surface topography measurement. Nanomanufacturing and Metrology, 3, 68-76. https://doi.org/10.1007/s41871-020-00057-4
  • [10] Leach, R. (Ed.). (2011). Optical Measurement of Surface Topography (Vol. 8). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-12012-1
  • [11] Maculotti, G., Feng, X., Galetto, M., & Leach, R. (2018). Noise evaluation of a point autofocus surface topography measuring instrument. Measurement Science and Technology, 29(6), 065008. https://doi.org/10.1088/1361-6501/aab528
  • [12] De Groot, P. J. (2017). The meaning and measure of vertical resolution in optical surface topography measurement. Applied Sciences, 7(1), 54. https://doi.org/10.3390/app7010054
  • [13] Haitjema, H., & Morel, M. A. A. (2005). Noise bias removal in profile measurements. Measurement, 38(1), 21-29. https://doi.org/10.1016/j.measurement.2005.02.002
  • [14] Leach, R., Haitjema, H., Su, R., & Thompson, A. (2020). Metrological characteristics for the calibration of surface topography measuring instruments: a review. Measurement Science and Technology, 32(3), 032001. https://doi.org/10.1088/1361-6501/abb54f
  • [15] DIN. (2008). Optical measurement and microtopographies - Calibration of interference microscopes and depth measurement standards for roughness measurement (VDI/VDE 2655 Blatt 1.1).
  • [16] DIN. (2010). Optical measurement of microtopography - Calibration of confocal microscopes and depth setting standards for roughness measurement (VDI/VDE 2655 Blatt 1.2).
  • [17] de Groot, P., & DiSciacca, J. (2018, August). Surface-height measurement noise in interference microscopy. Interferometry XIX (Vol. 10749, p. 107490Q). International Society for Optics and Photonics. https://doi.org/10.1117/12.2323900
  • [18] 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
  • [19] International Organization for Standardization. (2012). Geometrical product specifications (GPS) - Surface texture: Areal - Part 3: Specification operators (ISO 25178-3:2012).
  • [20] Blateyron, F. (2014, May). Good practices for the use of areal filters. Proc. 3rd Seminar on Surface Metrology of the Americas.
  • [21] 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
  • [22] 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
  • [23] Podulka, P. (2020). Comparisons of envelope morphological filtering methods and various regular algorithms for surface texture analysis. Metrology and Measurement Systems, 27(2), 243-263. https://doi.org/10.24425/mms.2020.132772
  • [24] Podulka, P. (2021). Reduction of Influence of the High-Frequency Noise on the Results of Surface Topography Measurements. Materials, 14(2), 333. https://doi.org/10.3390/ma14020333
  • [25] Todhunter, L., Leach, R., & Blateyron, F. (2020). Mathematical approach to the validation of surface texture filtration software. Surface Topography: Metrology and Properties, 8(4), 045017. https://doi.org/10.1088/2051-672X/abc0fb
  • [26] Vanrusselt, M., & Haitjema, H. (2020). Reduction of noise bias in 2.5 D surface measurements. In Proceedings of Euspen’s 20th International Conference & Exhbition, 277-281. European Society for Precision Engineering; Nothampton.
  • [27] Gomez, C., Su, R., Lawes, S., & Leach, R. (2019). Comparison of two noise reduction methods in coherence scanning interferometry for surface measurement. The 14th International Symposium on Measurement Technology and Intelligent Instruments. 778
  • [28] Sánchez, Á. R., Thompson, A., Körner, L., Brierley, N., & Leach, R. (2020). Review of the influence of noise in X-ray computed tomography measurement uncertainty. Precision Engineering, 66, 382-391. https://doi.org/10.1016/j.precisioneng.2020.08.004
  • [29] confovis GmbH. Structured Illumination Microscopy. https://www.confovis.com/en/optical-measurement
  • [30] International Organization for Standardization. (2012). Geometrical product specifications (GPS) - Surface texture: Areal - Part 2: Terms, definitions and surface texture parameters (ISO 25178-2:2012).
  • [31] 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).
  • [32] Leach, R., Haitjema, H., & Giusca, C. (2019). A metrological characteristics approach to uncertainty in surface metrology. Optical Inspection of Microsystems, 73-91. CRC Press.
  • [33] Haitjema, H. (2015). Uncertainty in measurement of surface topography. Surface Topography: Metrology and Properties, 3(3), 035004. https://doi.org/10.1088/2051-672X/3/3/035004
  • [34] Yang, Z., Kessel, A., & Häusler, G. (2015). Better 3D Inspection with Structured Illumination: Signal Formation and Precision. Applied Optics, 54(22), 6652-6660. https://doi.org/10.1364/AO.54.006652
  • [35] 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
  • [36] Zhou, Y., Troutman, J., Evans, C., & Davies, A. (2014, June). Using the random ball test to calibrate slope dependent errors in optical profilometry. Optical Fabrication and Testing, OW4B-2. Optical Society of America. https://doi.org/10.1364/OFT.2014.OW4B.2
Uwagi
1. The author Zhen Li acknowledges the Chinese Scholarship Council (CSC) for funding his doctoral study.
2. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ba1ed5c9-877b-4c18-a94d-a337e3362238
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