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Proceedings Paper

Investigation of microwave tomographic imaging techniques for industrial processes
Author(s): Z. Wu; Abdelhakim H. Boughriet; Hugh McCann; L. E. Davis; A. T. Nugroho
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Paper Abstract

Microwave tomographic imaging techniques have mainly been studied for medical applications in the past two decades. In recent years, however, there has been increased interest in the application of microwave imaging techniques for industrial processes or multiphase flows. In the medical case, water has been used as the background material, with microwave antennas and the object immersed in water, and the contrast of the object is measured against the dielectric properties of water. For industrial application, it is more convenient to use air as the background medium. However, this leads to a large contrast problem if the material being imaged contains a large amount of water. Consequently, the image reconstruction algorithms need to be more adaptive to the level of contrast and uncertainty in the initial guessed values in the iterative reconstruction process. The electromagnetic noise in the open air environment would usually be higher than that in water as a result of the surrounding industrial noise, and the near field region is much larger in air than that in water at the same operating frequency. Therefore, the algorithms need to be less sensitive to the effect of noise. In this paper, two algorithms based on the Newton- Kantorovich and Conjugate Gradient error minimisation methods are investigated with a view to their applications in the imaging of industrial processes using air as the background medium. The results on the effect of noise and the images reconstructed using the algorithms are presented.

Paper Details

Date Published: 2 February 2001
PDF: 8 pages
Proc. SPIE 4188, Process Imaging for Automatic Control, (2 February 2001); doi: 10.1117/12.417172
Show Author Affiliations
Z. Wu, Univ. of Manchester Institute of Science and Technology (United Kingdom)
Abdelhakim H. Boughriet, Univ. of Manchester Institute of Science and Technology (United Kingdom)
Hugh McCann, Univ. of Manchester Institute of Science and Technology (United Kingdom)
L. E. Davis, Univ. of Manchester Institute of Science and Technology (United Kingdom)
A. T. Nugroho, Univ. of Manchester Institute of Science and Technology (United Kingdom)


Published in SPIE Proceedings Vol. 4188:
Process Imaging for Automatic Control
Hugh McCann; David M. Scott, Editor(s)

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