{"title":"Diagnosis of Mechanical and Electrical Faults in Electric Machines Using a Lightweight Frequency-Scaled Convolutional Neural Network","authors":"Arta Mohammad-Alikhani, Babak Nahid-Mobarakeh, Min-Fu Hsieh","doi":"10.1109/tec.2024.3490736","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":13211,"journal":{"name":"IEEE Transactions on Energy Conversion","volume":"63 1","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Energy Conversion","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/tec.2024.3490736","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
期刊介绍：
The IEEE Transactions on Energy Conversion includes in its venue the research, development, design, application, construction, installation, operation, analysis and control of electric power generating and energy storage equipment (along with conventional, cogeneration, nuclear, distributed or renewable sources, central station and grid connection). The scope also includes electromechanical energy conversion, electric machinery, devices, systems and facilities for the safe, reliable, and economic generation and utilization of electrical energy for general industrial, commercial, public, and domestic consumption of electrical energy.
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