[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126999-en":3,"doc-seo-126999-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},126999,687207024643,"Oliver","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","A Machine Learning-Based Inter-Turn Short-Circuit Diagnosis for Multi-Three-Phase Brushless Motors","The paper presents an artificial intelligence-based short-circuit (SC) diagnosis strategy for a multi-three-phase brushless motor drive using machine learning (ML). A detailed electrical-machine model is built via finite-element simulations to reproduce inter-turn SC and extra-turn (ET) fault scenarios, generating data for ML training. Trained models are validated with experimental measurements from a multiphase-drive prototype. The proposed ML approach enables health monitoring and distinguishes two fault types while localizing faulty coils effectively.","Alma Mater Studiorum Università di Bologna Archivio istituzionale della ricerca  \nA Machine-Learning-Based Interturn Short-Circuit Diagnosis for Multi-Three-Phase Brushless Motors  \nThis is the final peer-reviewed author’s accepted manuscript (postprint) of the following publication:  \nPublished Version:  \nFemia, A. , Sala, G. , Vancini, L. , Rizzoli, G. , Mengoni, M. , Zarri, L. , et al. (2023) . A Machine-Learning-Based Interturn Short-Circuit Diagnosis for Multi-Three-Phase Brushless Motors. IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN INDUSTRIAL ELECTRONICS, 4(3), 855-865 [10.1109/JESTIE.2023.3258345] .  \nAvailability:  \nThis version is available at: [https://hdl.handle.net/11585/950633 since: 2024-02-27](https://hdl.handle.net/11585/950633 since: 2024-02-27)[ ](https://hdl.handle.net/11585/950633 since: 2024-02-27)Published:  \nDOI: [http://doi.org/10.1109/JESTIE.2023.3258345](http://doi.org/10.1109/JESTIE.2023.3258345)  \nTerms of use:  \nSome rights reserved. The terms and conditions for the reuse of this version of the manuscript are  \nspecified in the publishing policy. For all terms of use and more information see the publisher's website.  \nThis item was downloaded from IRIS Università di Bologna ( [https://cris.unibo.it/](https://cris.unibo.it/) ) .  \nWhen citing, please refer to the published version.  \n(Article begins on next page)  \n17 October 2024  \nThis is the final peer-reviewed accepted manuscript of:  \nA . Femia et al., \"A Machine-Learning-Based Interturn Short-Circuit Diagnosis for Multi-Three-Phase Brushless Motors,\" in IEEE Journal of Emerging and Selected Topics in Industrial Electronics, vol. 4, no. 3, pp. 855-865, July 2023  \nThe final published version is available online at:  \n[https://doi.org/10.1109/JESTIE.2023.3258345](https://doi.org/10.1109/JESTIE.2023.3258345)  \nTerms of use:  \nSome rights reserved. The terms and conditions for the reuse of this version of the manuscript are specified in the publishing policy. For all terms of use and more information see the publisher's website.  \nA Machine Learning-Based Inter-Turn Short-Circuit Diagnosis for Multi-Three-Phase Brushless Motors  \nAntonio Femia, Giacomo Sala, Member, IEEE, Luca Vancini, Gabriele Rizzoli, Michele Mengoni, Member, IEEE  \nLuca Zarri, Senior Member, IEEE, and Angelo Tani  \nAbstract—Over the past few years, Artificial Intelligence (AI) techniques have become one of the most exciting technologies of our age. This fascinating field paves the way for new possibilities and extends to almost all areas of industry and research. This paper illustrates a Short-Circuit (SC) diagnosis strategy for a multi-three-phase brushless AC motor drive based on Machine Learning (ML). A thorough model of the electrical machine is obtained through specific finite-element simulations and used to replicate various fault scenarios. This model quickly yields a large amount of data, which is then employed for training the ML algorithms. Once trained, the ML models are tested, with experimental data directly obtained from a prototype of multiphase drive, to verify the effectiveness of the diagnostic algorithms. The ML algorithms allow monitoring the health condition of the machine, distinguishing and localizing two types of faults, i.e., inter-turn SCs and Extra Turns (ETs), placed indifferent coils of the machine.  \nIndex Terms—Artificial intelligence, circuit fault, fault diagnosis, fault location, machine learning, multiphase drives, neural network.  \nI. INTRODUCTION  \nINTEREST in multiphase motors has significantly grown  \nin recent years due to a general increase in reliability requirements for industrial drives in various applications [1]–[3] . It has been proven that a multiphase drive can often continue to operate under fault conditions, albeit at reduced performance.  \nThe advantages of multiphase drives, such as the fault tolerance capability, combined with those of synchronous machines, such as high efficiency, high power density, and excellent dynam","cbCaitSuTbSPNzGN","https://ap.wps.com/l/cbCaitSuTbSPNzGN","pdf",8597788,1,13,"English","en",105,"# Abstract\n# I. Introduction\n## Background and motivation for multiphase motors\n## Rationale for ML-based fault diagnosis","[{\"question\":\"What problem does the paper address?\",\"answer\":\"It addresses short-circuit diagnosis in a multi-three-phase brushless motor drive, focusing on inter-turn short circuits and extra turns.\"},{\"question\":\"How is training data generated for the machine learning models?\",\"answer\":\"A thorough electrical-machine model is obtained through finite-element simulations to replicate multiple fault scenarios, producing data for ML training.\"},{\"question\":\"How are the ML diagnostic algorithms validated?\",\"answer\":\"The trained ML models are tested using experimental data collected from a prototype multiphase drive to verify diagnostic effectiveness.\"}]","A Machine Learning-Based Inter-Turn Short-Circuit Diagnosis for Multi-Three-Phase Brushless Motors | PDF",1785936169,33,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-machine-learning-based-inter-turn-short-circuit-diagnosis-for-multi-three-phase-brushless-motors","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-machine-learning-based-inter-turn-short-circuit-diagnosis-for-multi-three-phase-brushless-motors/126999/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the paper address?","Question",{"text":75,"@type":76},"It addresses short-circuit diagnosis in a multi-three-phase brushless motor drive, focusing on inter-turn short circuits and extra turns.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is training data generated for the machine learning models?",{"text":80,"@type":76},"A thorough electrical-machine model is obtained through finite-element simulations to replicate multiple fault scenarios, producing data for ML training.",{"name":82,"@type":73,"acceptedAnswer":83},"How are the ML diagnostic algorithms validated?",{"text":84,"@type":76},"The trained ML models are tested using experimental data collected from a prototype multiphase drive to verify diagnostic effectiveness.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]