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

Zhang, Hong, Gao, Bin, Tian, Gui Yun, Woo, Wai Lok and Simm, Anthony (2014) Spatial-Frequency Spectrum Characteristics Analysis With Different Lift-Offs for Microwave Nondestructive Testing and Evaluation Using Itakura-Saito Nonnegative Matrix Factorization. IEEE Sensors Journal, 14 (6). pp. 1822-1830. ISSN 1530-437X

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Defects detection, microwave nondestructive testing and evaluation, open-ended waveguide, nonnegative matrix factorization
Subjects:	H600 Electronic and Electrical Engineering
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Becky Skoyles
Date Deposited:	01 May 2019 08:19
Last Modified:	10 Oct 2019 19:31
URI:	http://nrl.northumbria.ac.uk/id/eprint/39113

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