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Lookup NU author(s): Professor Bin Gao,
Professor Gui Yun Tian
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2019 Elsevier B.V. Aluminum alloy is widely used in industry. Generally, the ultrasound testing as one of the non-destructive testing technologies has been applied to the metal sheet inspection for guarantying the quality of the production. However there exist challenges if only single ultrasound testing is applied. The near-field area of ultrasonic method remains limitation for detection. This paper investigates a robust data fusion model for comprehensive defects detection by hybriding inductive thermography and ultrasound testing in dynamic scanning. The proposed data fusion architecture is based on feature layer construction and it is able to cover the entire inspection from the surface, near surface and inside of the specimen. The experiment result demonstrates that the measurement of defects position and contour is accurate and reliable. It is easier to achieve automatic inspection through visualization and feature extraction. This method is effective and reliable for comprehensive detect and measurement metal plate.
Author(s): Xiao X, Gao B, Tian GY, Wang KQ
Publication type: Article
Publication status: Published
Journal: Infrared Physics and Technology
Print publication date: 01/09/2019
Online publication date: 03/07/2019
Acceptance date: 30/06/2019
Date deposited: 23/09/2019
ISSN (print): 1350-4495
Publisher: Elsevier BV
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