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Abstract

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.
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Authors and Affiliations

Zhen Li
1
ORCID: ORCID
Sophie Gröger
1

  1. Chemnitz University of Technology, Department of Production Measuring Technology, Reichenhainer Straße 70, 09126 Chemnitz, Germany
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Abstract

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.
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Bibliography

[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 in optical 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).Areviewof 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.
[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
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Authors and Affiliations

Zhen Li
1
ORCID: ORCID
Sophie Gröger
1

  1. Chemnitz University of Technology, Department of Production Measuring Technology, Reichenhainer Straße 70, 09126 Chemnitz, Germany
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Abstract

The primary aim of this paper is to study the optimization of rigid frame bridge parameters. With a three-span continuous rigid frame bridge as the engineering background, finite element models were established. Then an index about bridge force condition was proposed to calculate the optimal side-to-mid span ratio with different side-to-mid span ratio parameters. Based on the ratio, the values of the girder depth at the pier and the bottom curve degree of the box-girder were taken as parameters in their common ranges for further optimization. A comprehensive multi-objective evaluation index correlated with the mid-span section stress, the mid-span deflection, and the concrete consumption was proposed to do fine optimization through the genetic algorithm method. The result of this study shows that the genetic algorithm is an effective method for bridge optimization and could provide better girder design parameter combinations for the comprehensive performance, and the optimal result could be obtained in the continuous parameter definition domains. It also shows that a larger girder depth at the pier to span ratio and a smaller curve degree in their common ranges should be taken for the bridge’s comprehensive performance.
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Authors and Affiliations

Yao Lu
1
Dejian Li
1
Che Yao
1
Zhen Li
1
ORCID: ORCID

  1. Central South University, School of Civil Engineering, 68 South Shaoshan Road, Railway Campus CSU, 410075, Changsha, China
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Abstract

The coarse-grained heat-affected zone specimens of X80 pipeline steel were produced by welding thermal simulation under different heat inputs of 10, 30, and 55 kJ/cm to study the effects of heat input on microstructure evolution and corrosion characterization. The corrosion resistance of coarse-grained heat-affected zones was poorer than that of base metal due to less homogenous in the former. For 10 kJ/cm coarse-grained heat-affected zone, the corrosion resistance was poorer than the others due to the more adsorption hydrogen around the needle-like martensite/austenite constituents and greater galvanic driving force between the needle-like martensite/austenite constituents and ferrite. In carbonate/bicarbonate solution, better corrosion resistance for coarse-grained heat-affected zones was obtained when the heat input is 30 kJ/cm, which can be attributed to the severe coarse martensite/austenite constituents for 55 kJ/cm coarse-grained heat-affected zone. In the H2S environment, the better corrosion resistance for coarse-grained heat-affected zone was obtained when the heat input is 55 kJ/cm, which can be attributed to the protective effect of corrosion products. In addition, the high content of M/A constituents for 30 kJ/cm CGHAZ was good for hydrogen adsorption, which was adverse to the corrosion resistance in acid environments.
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Authors and Affiliations

Xue-Mei Wang
1 2
ORCID: ORCID
Wei Zhao
1 2 3
ORCID: ORCID
Kai Chen
1 2
ORCID: ORCID
Zhen Li
1 2
ORCID: ORCID

  1. Qilu University of Technology (Shandong Academy of Sciences), School of Mechanical & Automotive Engineering, China
  2. Shandong Institute of Mechanical Design and Research, China
  3. School of Materials Science and Engineering, Tianjin University, China

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