Staff View: An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms

An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms

This paper presents an automatic visual inspection of exterior surface defects of oil tanks using unmanned aerial vehicles (UAVs) and image processing with two cascading fuzzy logic algorithms. Corrosion is one of the defects that has a serious effect on the safety of the surface of oil and gas tank...

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Main Authors:	Mohammed A. H., Ali, Muhammad, Baggash, Jaloliddin, Rustamov, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Najm Al-Deen N., Abdo, Mubarak H. G., Abdo, Talep S., Mohammed, Ameen A., Hasan, Ali N., Abdo, Sherzod, Turaev, Yusoff, Nukman
Format:	Article
Language:	English English
Published:	Multidisciplinary Digital Publishing Institute (MDPI) 2023
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/103862/2/103862_An%20Automatic%20Visual%20Inspection%20of%20Oil.pdf http://irep.iium.edu.my/103862/8/103862_An%20Automatic%20Visual%20Inspection%20of%20Oil_SCOPUS.pdf http://irep.iium.edu.my/103862/ https://www.mdpi.com/2504-446X/7/2/133/pdf?version=1677221749 https://doi.org/10.3390/drones7020133
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id	my.iium.irep.103862
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spelling	my.iium.irep.1038622023-06-21T01:20:42Z http://irep.iium.edu.my/103862/ An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms Mohammed A. H., Ali Muhammad, Baggash Jaloliddin, Rustamov Abdulghafor, Rawad Abdulkhaleq Abdulmolla Najm Al-Deen N., Abdo Mubarak H. G., Abdo Talep S., Mohammed Ameen A., Hasan Ali N., Abdo Sherzod, Turaev Yusoff, Nukman T Technology (General) This paper presents an automatic visual inspection of exterior surface defects of oil tanks using unmanned aerial vehicles (UAVs) and image processing with two cascading fuzzy logic algorithms. Corrosion is one of the defects that has a serious effect on the safety of the surface of oil and gas tanks. At present, human inspection, and climbing robots inspection are the dominant approach for rust detection in oil and gas tanks. However, there are many shortcomings to this approach, such as taking longer, high cost, and covering less surface area inspection of the tank. The purpose of this research is to detect the rust in oil tanks by localizing visual inspection technology using UAVs, as well as to develop algorithms to distinguish between defects and noise. The study focuses on two basic aspects of oil tank inspection through the images captured by the UAV, namely, the detection of defects and the distinction between defects and noise. For the former, an image processing algorithm was developed to improve or remove noise, adjust the brightness of the captured image, and extract features to identify defects in oil tanks. Meanwhile, for the latter aspect, a cascading fuzzy logic algorithm and threshold algorithm were developed to distinguish between defects and noise levels and reduce their impact through three stages of processing: The first stage of fuzzy logic aims to distinguish between defects and low noise generated by the appearance of objects on the surface of the tank, such as trees or stairs, and reduce their impact. The second stage aims to distinguish between defects and medium noise generated by shadows or the presence of small objects on the surface of the tank and reduce their impact. The third stage of the thresholding algorithm aims to distinguish between defects and high noise generated by sedimentation on the surface of the tank and reduce its impact. The samples were classified based on the output of the third stage of the threshold process into defective or non-defective samples. The proposed algorithms were tested on 180 samples and the results show its superiority in the inspection and detection of defects with an accuracy of 83%. Multidisciplinary Digital Publishing Institute (MDPI) 2023-02-13 Article PeerReviewed application/pdf en http://irep.iium.edu.my/103862/2/103862_An%20Automatic%20Visual%20Inspection%20of%20Oil.pdf application/pdf en http://irep.iium.edu.my/103862/8/103862_An%20Automatic%20Visual%20Inspection%20of%20Oil_SCOPUS.pdf Mohammed A. H., Ali and Muhammad, Baggash and Jaloliddin, Rustamov and Abdulghafor, Rawad Abdulkhaleq Abdulmolla and Najm Al-Deen N., Abdo and Mubarak H. G., Abdo and Talep S., Mohammed and Ameen A., Hasan and Ali N., Abdo and Sherzod, Turaev and Yusoff, Nukman (2023) An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms. Drones, 7 (2). pp. 1-25. ISSN 2504-446X https://www.mdpi.com/2504-446X/7/2/133/pdf?version=1677221749 https://doi.org/10.3390/drones7020133
institution	Universiti Islam Antarabangsa Malaysia
building	IIUM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	International Islamic University Malaysia
content_source	IIUM Repository (IREP)
url_provider	http://irep.iium.edu.my/
language	English English
topic	T Technology (General)
spellingShingle	T Technology (General) Mohammed A. H., Ali Muhammad, Baggash Jaloliddin, Rustamov Abdulghafor, Rawad Abdulkhaleq Abdulmolla Najm Al-Deen N., Abdo Mubarak H. G., Abdo Talep S., Mohammed Ameen A., Hasan Ali N., Abdo Sherzod, Turaev Yusoff, Nukman An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms
description	This paper presents an automatic visual inspection of exterior surface defects of oil tanks using unmanned aerial vehicles (UAVs) and image processing with two cascading fuzzy logic algorithms. Corrosion is one of the defects that has a serious effect on the safety of the surface of oil and gas tanks. At present, human inspection, and climbing robots inspection are the dominant approach for rust detection in oil and gas tanks. However, there are many shortcomings to this approach, such as taking longer, high cost, and covering less surface area inspection of the tank. The purpose of this research is to detect the rust in oil tanks by localizing visual inspection technology using UAVs, as well as to develop algorithms to distinguish between defects and noise. The study focuses on two basic aspects of oil tank inspection through the images captured by the UAV, namely, the detection of defects and the distinction between defects and noise. For the former, an image processing algorithm was developed to improve or remove noise, adjust the brightness of the captured image, and extract features to identify defects in oil tanks. Meanwhile, for the latter aspect, a cascading fuzzy logic algorithm and threshold algorithm were developed to distinguish between defects and noise levels and reduce their impact through three stages of processing: The first stage of fuzzy logic aims to distinguish between defects and low noise generated by the appearance of objects on the surface of the tank, such as trees or stairs, and reduce their impact. The second stage aims to distinguish between defects and medium noise generated by shadows or the presence of small objects on the surface of the tank and reduce their impact. The third stage of the thresholding algorithm aims to distinguish between defects and high noise generated by sedimentation on the surface of the tank and reduce its impact. The samples were classified based on the output of the third stage of the threshold process into defective or non-defective samples. The proposed algorithms were tested on 180 samples and the results show its superiority in the inspection and detection of defects with an accuracy of 83%.
format	Article
author	Mohammed A. H., Ali Muhammad, Baggash Jaloliddin, Rustamov Abdulghafor, Rawad Abdulkhaleq Abdulmolla Najm Al-Deen N., Abdo Mubarak H. G., Abdo Talep S., Mohammed Ameen A., Hasan Ali N., Abdo Sherzod, Turaev Yusoff, Nukman
author_facet	Mohammed A. H., Ali Muhammad, Baggash Jaloliddin, Rustamov Abdulghafor, Rawad Abdulkhaleq Abdulmolla Najm Al-Deen N., Abdo Mubarak H. G., Abdo Talep S., Mohammed Ameen A., Hasan Ali N., Abdo Sherzod, Turaev Yusoff, Nukman
author_sort	Mohammed A. H., Ali
title	An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms
title_short	An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms
title_full	An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms
title_fullStr	An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms
title_full_unstemmed	An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms
title_sort	automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms
publisher	Multidisciplinary Digital Publishing Institute (MDPI)
publishDate	2023
url	http://irep.iium.edu.my/103862/2/103862_An%20Automatic%20Visual%20Inspection%20of%20Oil.pdf http://irep.iium.edu.my/103862/8/103862_An%20Automatic%20Visual%20Inspection%20of%20Oil_SCOPUS.pdf http://irep.iium.edu.my/103862/ https://www.mdpi.com/2504-446X/7/2/133/pdf?version=1677221749 https://doi.org/10.3390/drones7020133
_version_	1769841809164337152
score	13.211869

An automatic visual inspection of oil tanks exterior surface using unmanned aerial vehicle with image processing and cascading fuzzy logic algorithms

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