A Novel Light Sectioning Vision System for a Three Dimensional Surface Roughness Assessment. | ||||
| MEJ- Mansoura Engineering Journal | ||||
| Article 5, Volume 35, Issue 3, September 2010, Page 14-26 PDF (236.61 K) | ||||
| Document Type: Research Studies | ||||
| DOI: 10.21608/bfemu.2020.125069 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Ossama B. Abouelatta  
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| Professor of Production Engineering and Mechanical Design Department., Faculty of Engineering., El-Mansoura University., 35516 Mansoura., Egypt. | ||||
| Abstract | ||||
| Standard roughness measurement procedures depend heavily on stylus instruments which have only limited flexibility in handling different parts. On the other hand, optical non-contact techniques are very interesting for 3D characterization of sensitive and complex engineering surfaces. In this study, a new approach is introduced to measure surface roughness in three dimensions by combining a light sectioning microscope and a computer vision system. This approach has the advantages of being non-contact, fast and cheap. A prototype version of a user interface program, currently named SR3D Vision, has been developed to manage three dimensional surface roughness measurements. A light sectioning microscope is used to view roughness profiles of the specimens to be Measured and the vision system is used to capture images for successive profiles. This program has been totally developed in-house using MatlabTM software to analyze the captured images through four main modules: (Measurement controller, Profile or surface extraction, 2D roughness parameters calculation and 3D roughness parameters calculation). The system has been calibrated for metric units and verified using standard specimens. In addition, the system was used to measure various samples machined by different operations and the results were compared with a commercial software and a web-based surface metrology algorithm testing system. The accuracy of the system was verified and proved to be within ±4.8% compared with these systems. | ||||
| Keywords | ||||
| 3D surface roughness; Computer vision; Light sectioning | ||||
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