Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry

A Master of Science thesis in Electrical Engineering by Mohammad Abu Laila entitled, “Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry”, submitted in September 2021. Thesis advisor is Dr. Nasser Qaddoumi and thesis co-advisor is Dr. Amer Zakaria. Soft copy is availab...

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Main Author: Abu Laila, Mohammad (author)
Format: doctoralThesis
Published: 2021
Subjects:
Online Access:http://hdl.handle.net/11073/21608
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author Abu Laila, Mohammad
author_facet Abu Laila, Mohammad
author_role author
dc.contributor.none.fl_str_mv Qaddoumi, Nasser
Zakaria, Amer
dc.creator.none.fl_str_mv Abu Laila, Mohammad
dc.date.none.fl_str_mv 2021-09
2022-01-26T08:57:44Z
2022-01-26T08:57:44Z
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.identifier.none.fl_str_mv 35.232-2021.61
http://hdl.handle.net/11073/21608
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Non-metallics
Microwave imaging
Non-destructive testing
Nearfield
Waveguide
Rectangular waveguide
Field distribution
Point spread function (PSF)
PSF
Convolution
Deconvolution
dc.title.none.fl_str_mv Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Electrical Engineering by Mohammad Abu Laila entitled, “Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry”, submitted in September 2021. Thesis advisor is Dr. Nasser Qaddoumi and thesis co-advisor is Dr. Amer Zakaria. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
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identifier_str_mv 35.232-2021.61
language_invalid_str_mv en_US
network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/21608
publishDate 2021
repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas IndustryAbu Laila, MohammadNon-metallicsMicrowave imagingNon-destructive testingNearfieldWaveguideRectangular waveguideField distributionPoint spread function (PSF)PSFConvolutionDeconvolutionA Master of Science thesis in Electrical Engineering by Mohammad Abu Laila entitled, “Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry”, submitted in September 2021. Thesis advisor is Dr. Nasser Qaddoumi and thesis co-advisor is Dr. Amer Zakaria. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The increased demand for energy in the modern industrialized world pushed towards the search for suitable alternatives to existing technologies and materials used in the oil and gas industry. The use of non-metallics components in the oil and gas industry has grown in popularity in recent years for their durability and light-weightiness. These components may fail in many predictable and unpredictable ways in-service or due to manufacturing errors. Since these components are being used for sensitive applications, there is an increasing demand for suitable and accurate inspection and evaluation techniques of such components. Many non-destructive testing techniques have been developed in the past. However, such techniques suffer from significant limitations, including low image quality, slow response, and physical bulkiness. One of the most reliable and well-tested methods is the near-field microwave scanning system, using various near-field electromagnetic probes, e.g., rectangular and circular waveguides. This thesis proposes the enhancements of the imaging capabilities of rectangular waveguides microwave systems using deconvolution methods involving a function called the point spread function. The electric and magnetic field distributions are derived and solved in the near-field region of rectangular waveguides to derive the point spread function. In addition, formulas for the scattered electric and magnetic fields are derived and simplified. These results are used to derive a formula for the point spread function analytically. The point spread function is used for the deconvolution process on scanned images from a microwave scanning system. This process is tested on various simulations and reproductions of real-world defects. The deconvolution process is found to increase the accuracy of the reconstructed images compared to the actual defects. In addition, there are very noticeable improvements in the resolution of imaging systems, increasing their ability to distinguish closely-spaced defects.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE)Qaddoumi, NasserZakaria, Amer2022-01-26T08:57:44Z2022-01-26T08:57:44Z2021-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdf35.232-2021.61http://hdl.handle.net/11073/21608en_USoai:repository.aus.edu:11073/216082025-11-13T07:21:24Z
spellingShingle Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry
Abu Laila, Mohammad
Non-metallics
Microwave imaging
Non-destructive testing
Nearfield
Waveguide
Rectangular waveguide
Field distribution
Point spread function (PSF)
PSF
Convolution
Deconvolution
status_str publishedVersion
title Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry
title_full Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry
title_fullStr Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry
title_full_unstemmed Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry
title_short Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry
title_sort Microwave Imaging System for Non-Metallics Inspection in the Oil and Gas Industry
topic Non-metallics
Microwave imaging
Non-destructive testing
Nearfield
Waveguide
Rectangular waveguide
Field distribution
Point spread function (PSF)
PSF
Convolution
Deconvolution
url http://hdl.handle.net/11073/21608