{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:17:18Z","timestamp":1774628238064,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T00:00:00Z","timestamp":1612224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundamental Research Funding for the Central Universities of Ministry of Education of China","award":["18D110408"],"award-info":[{"award-number":["18D110408"]}]},{"name":"[the Special Project Funding for the Shanghai Municipal Commission of Economy and Information Civil-Military Inosculation Project \u201cBig Data Management System of UAVs\u201d","award":["JMRH-2018-1042"],"award-info":[{"award-number":["JMRH-2018-1042"]}]},{"name":"the National Natural Science Foundation of China (NSFC","award":["18K10454"],"award-info":[{"award-number":["18K10454"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The early detection of damaged (partially broken) outdoor insulators in primary distribution systems is of paramount importance for continuous electricity supply and public safety. Unmanned aerial vehicles (UAVs) present a safer, autonomous, and efficient way to examine the power system components without closing the power distribution system. In this work, a novel dataset is designed by capturing real images using UAVs and manually generated images collected to overcome the data insufficiency problem. A deep Laplacian pyramid-based super-resolution network is implemented to reconstruct high-resolution training images. To improve the visibility of low-light images, a low-light image enhancement technique is used for the robust exposure correction of the training images. A different fine-tuning strategy is implemented for fine-tuning the object detection model to increase detection accuracy for the specific faulty insulators. Several flight path strategies are proposed to overcome the shuttering effect of insulators, along with providing a less complex and time- and energy-efficient approach for capturing a video stream of the power system components. The performance of different object detection models is presented for selecting the most suitable one for fine-tuning on the specific faulty insulator dataset. For the detection of damaged insulators, our proposed method achieved an F1-score of 0.81 and 0.77 on two different datasets and presents a simple and more efficient flight strategy. Our approach is based on real aerial inspection of in-service porcelain insulators by extensive evaluation of several video sequences showing robust fault recognition and diagnostic capabilities. Our approach is demonstrated on data acquired by a drone in Swat, Pakistan.<\/jats:p>","DOI":"10.3390\/s21030974","type":"journal-article","created":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T05:44:42Z","timestamp":1612244682000},"page":"974","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":69,"title":["Autonomous Vision-Based Primary Distribution Systems Porcelain Insulators Inspection Using UAVs"],"prefix":"10.3390","volume":"21","author":[{"given":"Ehab Ur","family":"Rahman","sequence":"first","affiliation":[{"name":"College of Information Science and Technology, Engineering Research Center of Digitized Textile &amp; Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China"}]},{"given":"Yihong","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Engineering Research Center of Digitized Textile &amp; Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5890-9370","authenticated-orcid":false,"given":"Sohail","family":"Ahmad","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Engineering Research Center of Digitized Textile &amp; Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China"}]},{"given":"Hafiz Ishfaq","family":"Ahmad","sequence":"additional","affiliation":[{"name":"School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor 79100, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3939-7303","authenticated-orcid":false,"given":"Sayed","family":"Jobaer","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Engineering Research Center of Digitized Textile &amp; Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,2]]},"reference":[{"key":"ref_1","unstructured":"Hassan, I.A.Q. 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