3D Defect detection using weighted principal component thermography. (May 2020)

• Record Type: Journal Article
• Authors: Sels, Seppe; Bogaerts, Boris; Verspeek, Simon; Ribbens, Bart; Steenackers, Gunther; Penne, Rudi; Vanlanduit, Steve
• Is Part Of: Optics and lasers in engineering. Volume 128(2020)
• Publication Date: 2020-05
• Subjects: Thermography -- 3D -- Matching -- Active thermography -- Pulsed thermography -- Principal component analysis -- Principal component thermography -- 3D Thermography -- Infrared imaging; Lasers in engineering -- Periodicals; Optical measurements -- Periodicals; Optics -- Periodicals; Lasers en ingénierie -- Périodiques; Mesures optiques -- Périodiques; Optique -- Périodiques; 621.36605
• DOI: 10.1016/j.optlaseng.2020.106039
• Languages: English
• ISSNs: 0143-8166

Abstract

Highlights: A thermal camera setup is used to detect defects in materials. A CAD matching procedure is used to map a 2D infrared image to a 3D cad file. With the 3D alignment a quality metric of the measurement is calculated. With this metric misclassifications are reduced. Abstract: Quantitive infrared thermography like active thermography is a non-destructive testing technique that is used to inspect surfaces of components for defects. A problem with infrared-based defect detection is that misclassifications based on geometrically dependent measurement characteristics can occur. This problem becomes more problematic with the inspection of complex 3D shapes. In this paper, a new infrared quality control procedure using a quality map is proposed that models the geometrically dependent measurement characteristics based on available CAD data and CAD matching techniques. Misclassifications are reduced by using this quality map in combination with a modified version of principal component thermography post-processing. We applied our proposed methodology on a prototype bicycle part and a plaster cast angel figurine. In these experiments, the procedure using quality maps is able to prevent false defect detection.