Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images
Measurement of surface roughness over a large area is a very challenging task due to the limitations with the existing techniques. Surface roughness measurement techniques including stylus and microscopy are limited by point-by-point data acquisition and a small field of view (FOV). In effect, any s...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2020
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| Online Access: | https://hdl.handle.net/10356/143976 |
| _version_ | 1811683455234211840 |
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| author | Haridas, Aswin Prabhathan, P. Pulkit, K. Chan, Kelvin Murukeshan, Vadakke Matham |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Haridas, Aswin Prabhathan, P. Pulkit, K. Chan, Kelvin Murukeshan, Vadakke Matham |
| author_sort | Haridas, Aswin |
| collection | NTU |
| description | Measurement of surface roughness over a large area is a very challenging task due to the limitations with the existing techniques. Surface roughness measurement techniques including stylus and microscopy are limited by point-by-point data acquisition and a small field of view (FOV). In effect, any solution that would subdue these limitations would be characterized by its full-field nature, large FOV, and the ability to acquire and process data at high speeds. To meet these requirements, large area speckle imaging has been used to obtain areal surface roughness parameters through the processing of spectrally correlated speckle images. An automated optical system is developed for surface roughness evaluation of components with large and curved surface areas. In order to extract areal surface roughness parameters from the captured set of images, processing algorithms are developed. The methodology is first validated using a comparator plate containing areas having an average surface roughness (Ra) ranging between 0.2 µm and 0.6 µm. Further, statistical significance tests are conducted to determine the main factors affecting system performance. The measurement results are compared and validated using a 3D optical microscope. The results obtained from the blind tests performed on aerospace component surfaces as large as 450mm×210mm are also presented. |
| first_indexed | 2024-10-01T04:13:00Z |
| format | Journal Article |
| id | ntu-10356/143976 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:13:00Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1439762023-03-04T17:22:42Z Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images Haridas, Aswin Prabhathan, P. Pulkit, K. Chan, Kelvin Murukeshan, Vadakke Matham School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Surface Roughness Optical Metrology Measurement of surface roughness over a large area is a very challenging task due to the limitations with the existing techniques. Surface roughness measurement techniques including stylus and microscopy are limited by point-by-point data acquisition and a small field of view (FOV). In effect, any solution that would subdue these limitations would be characterized by its full-field nature, large FOV, and the ability to acquire and process data at high speeds. To meet these requirements, large area speckle imaging has been used to obtain areal surface roughness parameters through the processing of spectrally correlated speckle images. An automated optical system is developed for surface roughness evaluation of components with large and curved surface areas. In order to extract areal surface roughness parameters from the captured set of images, processing algorithms are developed. The methodology is first validated using a comparator plate containing areas having an average surface roughness (Ra) ranging between 0.2 µm and 0.6 µm. Further, statistical significance tests are conducted to determine the main factors affecting system performance. The measurement results are compared and validated using a 3D optical microscope. The results obtained from the blind tests performed on aerospace component surfaces as large as 450mm×210mm are also presented. Economic Development Board (EDB) Ministry of Education (MOE) National Research Foundation (NRF) Accepted version This work was conducted within the Rolls-Royce@NTU Corporate Lab MRT 4.2 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. One of the authors, Patinharekandy Prabhathan contributed to this work during his role as a research fellow at Rolls-Royce@NTU Corporate Lab. Also, Aswin Haridas acknowledges NTU Singapore for the research scholarship received through NTU under the RSS scheme. 2020-10-06T02:06:14Z 2020-10-06T02:06:14Z 2020 Journal Article Haridas, A., Prabhathan, P., Pulkit, K., Chan, K., & Murukeshan, V. M. (2020). Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images. Applied Optics, 59(16), 5041-5051. doi:10.1364/AO.389227 1539-4522 https://hdl.handle.net/10356/143976 10.1364/AO.389227 32543501 16 59 5041 5051 en Applied Optics © 2020 Optical Society of America. All rights reserved. This paper was published in Applied Optics and is made available with permission of Optical Society of America. application/pdf |
| spellingShingle | Engineering::Mechanical engineering Surface Roughness Optical Metrology Haridas, Aswin Prabhathan, P. Pulkit, K. Chan, Kelvin Murukeshan, Vadakke Matham Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images |
| title | Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images |
| title_full | Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images |
| title_fullStr | Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images |
| title_full_unstemmed | Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images |
| title_short | Surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images |
| title_sort | surface roughness mapping of large area curved aerospace components through spectral correlation of speckle images |
| topic | Engineering::Mechanical engineering Surface Roughness Optical Metrology |
| url | https://hdl.handle.net/10356/143976 |
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