Applications of red-green-blue normalisation and interframe difference matrix in complex surface by eddy current pulsed thermography

Journal article (2018)

Authors

Z. Liu Wuhan University of Technology
Yong Du Wuhan University of Technology
Chao Zhu Wuhan University of Technology
Xuan Li Wuhan University of Technology
X. Jiang Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
Research Group
Transport Engineering and Logistics (Mechanical, Maritime and Materials Engineering) (TU Delft)
More Info
expand_more

Published Date

2018

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Transport Engineering and Logistics

Abstract

As a result of the influence of surface characteristics, it is difficult to identify cracks on complex surfaces using the conventional processing of a single-frame image that misses important infrared thermal image sequences. In this paper, the red-green-blue normalisation method and the interframe difference method are used to make full use of the sequences and to characterise infrared thermal images of cracks on complex surfaces. An experiment to prove the effectiveness of the detection method was carried out on weld steel and carbon fibre-reinforced polymer (CFRP) steel plate. The selected infrared thermal image was divided into an objective area and a background area according to the relationship between three parameters for red-green-blue and objective temperature. The targeted and interfering information of the objective area were separated and processed based on the interframe difference method. The index of crack detection was extracted from the interframe difference matrix, which was constructed from two selected infrared thermal images. This method takes into account the local and global spatial information of the image and the maximum crack length measurement error was approximately 6%.