{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T11:47:54Z","timestamp":1749815274911,"version":"3.37.3"},"reference-count":20,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004829","name":"Project of Sichuan Science and Technology Department","doi-asserted-by":"publisher","award":["2021YFG0313","2022YFS0518","2022ZHCG0035"],"award-info":[{"award-number":["2021YFG0313","2022YFS0518","2022ZHCG0035"]}],"id":[{"id":"10.13039\/501100004829","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Project of Sichuan Key Laboratory of Artificial Intelligence","award":["2020RZY03"],"award-info":[{"award-number":["2020RZY03"]}]},{"name":"Talent Introduction Project of Sichuan University of Light and Chemical Engineering","award":["2021RC12"],"award-info":[{"award-number":["2021RC12"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3327449","type":"journal-article","created":{"date-parts":[[2023,10,25]],"date-time":"2023-10-25T17:58:25Z","timestamp":1698256705000},"page":"119722-119732","source":"Crossref","is-referenced-by-count":4,"title":["Faulty Line Identification in AC\u2013DC Hybrid Grids Based on MTF and Improved Resnet"],"prefix":"10.1109","volume":"11","author":[{"given":"Hao","family":"Wu","sequence":"first","affiliation":[{"name":"Automation and Information Engineering, Sichuan University of Science & Engineering, Sichuan, Zigong, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2702-2357","authenticated-orcid":false,"given":"Weizhe","family":"Chen","sequence":"additional","affiliation":[{"name":"Automation and Information Engineering, Sichuan University of Science & Engineering, Sichuan, Zigong, China"}]},{"given":"Ziyuan","family":"Qi","sequence":"additional","affiliation":[{"name":"Automation and Information Engineering, Sichuan University of Science & Engineering, Sichuan, Zigong, China"}]},{"given":"Hong","family":"Song","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Aba Teachers College, Aba, China"}]},{"given":"Haipeng","family":"Tian","sequence":"additional","affiliation":[{"name":"Automation and Information Engineering, Sichuan University of Science & Engineering, Sichuan, Zigong, China"}]}],"member":"263","reference":[{"issue":"11","key":"ref1","first-page":"3107","article-title":"Confronting problem and challenge of large scale AC-DC hybrid power grid operation","volume":"39","author":"Dong","year":"2019","journal-title":"Proc. CSEE"},{"issue":"2","key":"ref2","first-page":"503","article-title":"Research on HVDC operation characteristics under influence of hybrid AC\/DC power grids","volume":"46","author":"Lu","year":"2022","journal-title":"Power Syst. Technol."},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRD.2011.2178079"},{"issue":"12","key":"ref4","first-page":"123","article-title":"Research on anti-transition resistance single-phase ground distance protection of ac-dc hybrid power system based on time-domain","volume":"31","author":"Rui","year":"2019","journal-title":"Proc. CSU-EPSA"},{"issue":"2","key":"ref5","first-page":"537","article-title":"DC fault detection scheme for multi-terminal hybrid AC\/DC distribution network based on current-limiting inductor voltage","volume":"43","author":"Xiaomin","year":"2019","journal-title":"Power Syst. Technol."},{"issue":"8","key":"ref6","first-page":"172","article-title":"Deep learning theory and its application to fault diagnosis of an electric machine","volume":"48","author":"Ding","year":"2020","journal-title":"Power Syst. Protection Control"},{"issue":"5","key":"ref7","first-page":"132","article-title":"Fault diagnosis for AC\/DC transmission system based on convolutional neural network","author":"Zhang","year":"2022","journal-title":"Automat. Electr. Power Syst."},{"volume-title":"Research on Fault Diagnosis of AC\/DC Hybrid Power Grid Based on Deep Learning","year":"2021","author":"Congzhou","key":"ref8"},{"issue":"2","key":"ref9","first-page":"53","article-title":"Novel fault feeder selection method for distribution network based on GAF and convolution neural network","volume":"35","author":"Lei","year":"2022","journal-title":"Proc. CSU-EPSA"},{"issue":"2","key":"ref10","first-page":"126","article-title":"Bearing fault diagnosis method based on MTF-CNN","volume":"42","author":"Zhao","year":"2023","journal-title":"J. Vib. Shock"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2014.06.009"},{"article-title":"Encoding time series as images for visual inspection and classification using tiled convolutional neural networks","volume-title":"Proc. Workshops 29th AAAI Conf. Artif. Intell.","author":"Wang","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"issue":"3","key":"ref14","first-page":"260","article-title":"Research on hazy image sharpening algorithm based on dual attention mechanism","volume":"34","author":"Wang","year":"2023","journal-title":"J. Optoelectron. Laser"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00165"},{"issue":"12","key":"ref16","first-page":"2213","article-title":"Diagnosis method of power grid fault based on deep stochastic configuration network","volume":"29","author":"Shao","year":"2022","journal-title":"Control Eng. China"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.eij.2023.05.002"},{"key":"ref18","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10295471.pdf?arnumber=10295471","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,14]],"date-time":"2024-03-14T10:27:43Z","timestamp":1710412063000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10295471\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3327449","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2023]]}}}