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dc.contributor.authorYahia, Mohamed
dc.contributor.authorGawai, Rahul
dc.contributor.authorAli, Tarig
dc.contributor.authorMortula, Maruf
dc.contributor.authorAlbasha, Lutfi
dc.contributor.authorLandolsi, Taha
dc.date.accessioned2022-06-06T09:52:22Z
dc.date.available2022-06-06T09:52:22Z
dc.date.issued2021
dc.identifier.citationM. Yahia, R. Gawai, T. Ali, M. M. Mortula, L. Albasha and T. Landolsi, "Non-Destructive Water Leak Detection Using Multitemporal Infrared Thermography," in IEEE Access, vol. 9, pp. 72556-72567, 2021, doi: 10.1109/ACCESS.2021.3078415.en_US
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/11073/23906
dc.description.abstractWaterleakage detection and localization in distribution networks pipelines is a challenge for utility companies. For this purpose, thermal Infrared Radiation (IR) techniques have been widely applied in the literature. However, the classical analysis of IR images has not been robust in detecting and locating leakage, due to presence of thermal anomalies such as shadows. In this study, to improve the detection and location accuracy, a digital image processing tool based on multitemporal IR is proposed. In multitemporal IR analysis, the variation of soil's temperature due to field temperature can be obtained; and hence; estimating variations due to water leakage would be more accurate. An experimental setup was built to evaluate the proposed multitemporal IR water leak detection method. In order to consider the temporal temperature variation due to water leakage and mitigate the field temperature effects, a luminance transformation of the IRimages was introduced. To determine the temporal temperature variation of the soil's surface due to the leakage, several metrics have been considered such as the difference, the ratio, the log-ratio and the coefficient variation (CV) images. Based on the experimental results, the log-ratio and the CVimages were the most robust metrics. Then, based on log-ratio or the CV image, a temporal variation image (TVI) that traduces the temporal IR luminance variation was introduced. The analysis of the TVI image showed that the CV image is less noisy than the log-ratio image, and can more accurately locate the leakage. Finally, based on TVI histogram, a threshold was de ned to classify the TVI image into leakage/non-leakage areas. Results showed that the proposed method is capable of accurately detecting and locating water leakage, which is an improvement to the false detections of spatial thermal IR analysis.en_US
dc.description.sponsorshipAmerican University of Sharjahen_US
dc.description.sponsorshipSmart City Research Instituteen_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.urihttps://doi.org/10.1109/ACCESS.2021.3078415en_US
dc.subjectSustainable development goals (SDG)en_US
dc.subjectNon-destructive evaluation (NDE)en_US
dc.subjectInfrared thermographyen_US
dc.subjectWater leak detectionen_US
dc.subjectMultitemporal analysisen_US
dc.titleNon-Destructive Water Leak Detection Using Multitemporal Infrared Thermographyen_US
dc.typeArticleen_US
dc.typePeer-Revieweden_US
dc.typePublished versionen_US
dc.identifier.doi10.1109/ACCESS.2021.3078415


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