Paper
16 November 2015 A comparative study of three vision systems for metal surface defect detection
Mehrube Mehrubeoglu, Petru-Aurelian Simionescu, Shawn Robinson, Lifford McLauchlan
Author Affiliations +
Abstract
In this paper we present a comparative analysis of three vision systems to nondestructively predict defects on the surfaces of aluminum castings. A hyperspectral imaging system, a thermal imager, and a digital color camera have been used to inspect aluminum metal cast surfaces. Hyperspectral imaging provides both spectral and spatial information, as each material produces specific spectral signatures which are also affected by surface texture. Thermal imager detects infrared radiation whereby hotspots can be investigated to identify possible trapped inclusions close to the surface, or other superficial defects. Finally, digital color images show apparent surface defects that can also be viewed with the naked eye but can be automated for fast and efficient data analysis. The surface defect locations predicted using the three systems are then verified by breaking the casings using a tensile tester. Of the three nondestructive methods, the thermal imaging camera was found to produce the most accurate predictions for defect location that caused breakage.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mehrube Mehrubeoglu, Petru-Aurelian Simionescu, Shawn Robinson, and Lifford McLauchlan "A comparative study of three vision systems for metal surface defect detection", Proc. SPIE 9611, Imaging Spectrometry XX, 96110L (16 November 2015); https://doi.org/10.1117/12.2190216
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Thermography

Hyperspectral imaging

Metals

Aluminum

Imaging systems

Digital photography

Defect detection

Back to Top