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Spatial-Frequency Spectrum Characteristics Analysis With Different Lift-Offs for Microwave Nondestructive Testing and Evaluation Using Itakura-Saito Nonnegative Matrix Factorization

Lookup NU author(s): Hong Zhang, Dr Bin Gao, Professor Gui Yun TianORCiD, Dr Wai Lok Woo, Anthony Simm


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Microwave nondestructive testing and evaluation (NDT&E) has tremendous potential for defect detection in metallic materials. In this paper: 1) an open-ended waveguide-based scanning system operating in the X-band (8.2-12.4 GHz) with a spatial-frequency feature extraction algorithm for defect detection at large lift-offs is presented; 2) a full mathematical derivation for modeling the spatial-frequency characteristics in the presence of defects and without defects is provided; and 3) a spatial-frequency feature extraction algorithm using the Itakura-Saito nonnegative matrix factorization is developed and investigated. The algorithm has the unique property of scale-invariance, which enables extraction of spatial-frequency features that are characterized by large dynamic ranges of energy. To evaluate the proposed technique, four defects in an aluminium plate with different depths (from 2 to 8 mm) and one tiny defect on a steel sample (0.45-mm width and 0.43-mm depth) have been examined. Experimental results have demonstrated that the proposed microwave NDT&E technique is capable of detecting defects at large lift-offs, with the potential of estimating the width and depth of defects, as well as classifying the different defect and nondefect areas.

Publication metadata

Author(s): Zhang H, Gao B, Tian GY, Woo WL, Simm A

Publication type: Article

Publication status: Published

Journal: IEEE Sensors Journal

Year: 2014

Volume: 14

Issue: 6

Pages: 1822-1830

Print publication date: 03/02/2014

ISSN (print): 1530-437X

ISSN (electronic): 1558-1748

Publisher: IEEE


DOI: 10.1109/JSEN.2014.2303832


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Funder referenceFunder name
Health Monitoring of Offshore Wind Farms
National Research Center of Sensors Engineering
Shenyang Academy of Instrumentation Company Ltd.
Cognitive-Networks-Enabled Transnational Proactive Healthcare
University of Electronic Science and Technology of China
2013HH0059Sichuan Science and Technology Department
51377015National Natural Science Foundation of China