Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
The added capabilities of Additive Manufacturing (AM) while processing metallic components have revolutionized the design and manufacturing flexibility of multitudes of aerospace components. However, AM being a stochastic process results in a degraded control of the surface topography of the printed...
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sg-ntu-dr.10356-1417622023-03-04T17:23:18Z Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope Haridas, Aswin Matham, Vadakke Murukeshan Crivoi, Alexandru Patinharekandy, Prabhathan Jen, Tan Ming Chan, Kelvin School of Mechanical and Aerospace Engineering Rolls-Royce @ NTU Corporate Laboratory Engineering::Mechanical engineering Surface Roughness White Light Imaging The added capabilities of Additive Manufacturing (AM) while processing metallic components have revolutionized the design and manufacturing flexibility of multitudes of aerospace components. However, AM being a stochastic process results in a degraded control of the surface topography of the printed structure and thus requires adequate finishing processes before implementation. Particularly, in the case of components having complex cross-sections and internal channels, none of the currently available technologies offer a solution for the measurement and certification of surface roughness parameters. In this context, this paper investigates a binary image processing technique applied to multiple white light images captured by a 0.3 mm diameter micro fiber endoscope. Further, AM sample surfaces generated by different build angles are investigated to demonstrate the advantages of the proposed technique. A surface roughness evaluation parameter is presented along with measurement results obtained using the Mitutoyo SJ400 (conventional profiler) and the Talyscan 150 (optical profiler). Economic Development Board (EDB) National Research Foundation (NRF) Accepted version This work was conducted within the Rolls-Royce@NTU Corporate Lab MRT 4.1 project with support from the National Research Foundation (NRF) Singapore under the Corp Lab@University Scheme. The authors are also grateful for the support from COLE EDB funding. 2020-06-10T08:16:24Z 2020-06-10T08:16:24Z 2018 Journal Article Haridas, A., Matham, V. M., Crivoi, A., Patinharekandy, P., Jen, T. M., & Chan, K. (2018). Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope. Optics and Lasers in Engineering, 110, 262-271. doi:10.1016/j.optlaseng.2018.05.026 0143-8166 https://hdl.handle.net/10356/141762 10.1016/j.optlaseng.2018.05.026 2-s2.0-85049333122 110 262 271 en Optics and Lasers in Engineering © 2018 Elsevier Ltd. All rights reserved. This paper was published in Optics and Lasers in Engineering and is made available with permission of Elsevier Ltd. application/pdf |
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Engineering::Mechanical engineering Surface Roughness White Light Imaging Haridas, Aswin Matham, Vadakke Murukeshan Crivoi, Alexandru Patinharekandy, Prabhathan Jen, Tan Ming Chan, Kelvin Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope |
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The added capabilities of Additive Manufacturing (AM) while processing metallic components have revolutionized the design and manufacturing flexibility of multitudes of aerospace components. However, AM being a stochastic process results in a degraded control of the surface topography of the printed structure and thus requires adequate finishing processes before implementation. Particularly, in the case of components having complex cross-sections and internal channels, none of the currently available technologies offer a solution for the measurement and certification of surface roughness parameters. In this context, this paper investigates a binary image processing technique applied to multiple white light images captured by a 0.3 mm diameter micro fiber endoscope. Further, AM sample surfaces generated by different build angles are investigated to demonstrate the advantages of the proposed technique. A surface roughness evaluation parameter is presented along with measurement results obtained using the Mitutoyo SJ400 (conventional profiler) and the Talyscan 150 (optical profiler). |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Haridas, Aswin Matham, Vadakke Murukeshan Crivoi, Alexandru Patinharekandy, Prabhathan Jen, Tan Ming Chan, Kelvin |
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Article |
author |
Haridas, Aswin Matham, Vadakke Murukeshan Crivoi, Alexandru Patinharekandy, Prabhathan Jen, Tan Ming Chan, Kelvin |
author_sort |
Haridas, Aswin |
title |
Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope |
title_short |
Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope |
title_full |
Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope |
title_fullStr |
Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope |
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Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope |
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surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope |
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2020 |
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https://hdl.handle.net/10356/141762 |
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