{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:38:14Z","timestamp":1774629494323,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T00:00:00Z","timestamp":1718928000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shanxi Provincial Higher Education Science and Technology Innovation Project","award":["2022L524"],"award-info":[{"award-number":["2022L524"]}]},{"name":"Shanxi Provincial Higher Education Science and Technology Innovation Project","award":["202102060301020"],"award-info":[{"award-number":["202102060301020"]}]},{"DOI":"10.13039\/501100013317","name":"Shanxi Provincial Key Research and Development Project","doi-asserted-by":"publisher","award":["2022L524"],"award-info":[{"award-number":["2022L524"]}],"id":[{"id":"10.13039\/501100013317","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013317","name":"Shanxi Provincial Key Research and Development Project","doi-asserted-by":"publisher","award":["202102060301020"],"award-info":[{"award-number":["202102060301020"]}],"id":[{"id":"10.13039\/501100013317","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Ice-covered transmission lines seriously affect the normal operation of the power transmission system. Resonance deicing based on different ice thicknesses is an effective method to solve the issue of ice-covered transmission lines. In order to obtain accurate ice thickness of transmission lines, this paper designs an ice thickness of transmission line recognition model based on Global Micro Strip Awareness Net (GMSA-Net) and proposes a Mixed Strip Convolution Module (MSCM) and a global micro awareness module (GMAM). The MSCM adapts to the shape of ice-covered transmission lines by using strip convolutions with different receptive fields, improving the encoder\u2019s ability to extract ice-covered features; the GMAM perceives through both global and micro parts, mining the connections between semantic information. Finally, the ice thickness of the generated segmented image is calculated using the method of regional pixel statistics. Experiments are conducted on the dataset of ice-covered transmission lines. The mean Intersection over Union (mIoU) of image segmentation reaches 96.4%, the balanced F-Score (F1-Score) is 98.1%, and the identification error of ice thickness is within 3.8%. Experimental results prove that this method can accurately identify the ice thickness of transmission lines, providing a control basis for the application of resonant deicing engineering.<\/jats:p>","DOI":"10.3390\/s24134053","type":"journal-article","created":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T11:10:28Z","timestamp":1718968228000},"page":"4053","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["GMSA-Net: A Transmission Line Ice Thickness Identification Network Based on Global Micro Strip Awareness"],"prefix":"10.3390","volume":"24","author":[{"given":"Yu","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China"},{"name":"Department of Automation, Taiyuan Institute of Technology, Taiyuan 030008, China"},{"name":"Shanxi Energy Internet Research Institute, Taiyuan 030032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1723-8262","authenticated-orcid":false,"given":"Yinke","family":"Dou","sequence":"additional","affiliation":[{"name":"College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China"},{"name":"Shanxi Energy Internet Research Institute, Taiyuan 030032, China"},{"name":"Key Laboratory of Cleaner Intelligent Control on Coal & Electricity, Ministry of Education, Taiyuan 030024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yangyang","family":"Jiao","sequence":"additional","affiliation":[{"name":"Shanxi Energy Internet Research Institute, Taiyuan 030032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liangliang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Shanxi Energy Internet Research Institute, Taiyuan 030032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongliang","family":"Guo","sequence":"additional","affiliation":[{"name":"Shanxi Energy Internet Research Institute, Taiyuan 030032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"105862","DOI":"10.1016\/j.ijepes.2020.105862","article-title":"Power transmission line inspection robots: A review, trends and challenges for future research","volume":"118","author":"Alhassan","year":"2020","journal-title":"Int. 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