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Статті в журналах з теми "Stator short circuit faults"
Zhang, Ming, Yi Ming Zhang, and Jiang Tao Tong. "Research on Stator Winding Inter Turn Short-Circuit Faults of Aeronautical Fault-Tolerant Machine Based on Maxwell 2D." Applied Mechanics and Materials 130-134 (October 2011): 119–23. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.119.
Повний текст джерелаAubert, Brice, Jérémi Régnier, Stéphane Caux, and Dominique Alejo. "Stator Winding Fault Diagnosis in Permanent Magnet Synchronous Generators Based on Short-Circuited Turns Identification Using Extended Kalman Filter." ACTA IMEKO 3, no. 4 (December 1, 2014): 4. http://dx.doi.org/10.21014/acta_imeko.v3i4.146.
Повний текст джерелаLiang, Hong, Yong Chen, Siyuan Liang, and Chengdong Wang. "Fault Detection of Stator Inter-Turn Short-Circuit in PMSM on Stator Current and Vibration Signal." Applied Sciences 8, no. 9 (September 16, 2018): 1677. http://dx.doi.org/10.3390/app8091677.
Повний текст джерелаTang, Jing, Jie Chen, Kan Dong, Yongheng Yang, Haichen Lv, and Zhigang Liu. "Modeling and Evaluation of Stator and Rotor Faults for Induction Motors." Energies 13, no. 1 (December 26, 2019): 133. http://dx.doi.org/10.3390/en13010133.
Повний текст джерелаAlawady, A. A., M. F. M. Yousof, N. Azis, and M. A. Talib. "Frequency response analysis technique for induction motor short circuit faults detection." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 3 (September 1, 2020): 1653. http://dx.doi.org/10.11591/ijpeds.v11.i3.pp1653-1659.
Повний текст джерелаPuzakov, Andrey. "Diagnosing of automotive alternators on thermal state." MATEC Web of Conferences 298 (2019): 00005. http://dx.doi.org/10.1051/matecconf/201929800005.
Повний текст джерелаGłowacz, Z., and J. Kozik. "Detection of Synchronous Motor Inter-Turn Faults Based on Spectral Analysis of Park’S Vector / Detekcja Zwarc Zwojowych W Silniku Synchronicznym Bazujaca Na Analizie Spektralnej Wektora Przestrzennego Pradu Twornika." Archives of Metallurgy and Materials 58, no. 1 (March 1, 2013): 19–23. http://dx.doi.org/10.2478/v10172-012-0144-y.
Повний текст джерелаFadzail, N. F., S. Mat Zali, M. A. Khairudin, and N. H. Hanafi. "Stator winding fault detection of induction generator based wind turbine using ANN." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 1 (July 1, 2020): 126. http://dx.doi.org/10.11591/ijeecs.v19.i1.pp126-133.
Повний текст джерелаAbdullateef, A. I., O. S. Fagbolagun, M. F. Sanusi, M. F. Akorede, and M. A. Afolayan. "Detection and Classification of Stator Short-Circuit Faults in Three-Phase Induction Motor." Journal of Applied Sciences and Environmental Management 24, no. 3 (April 23, 2020): 417–24. http://dx.doi.org/10.4314/jasem.v24i3.3.
Повний текст джерелаBouakoura, Mohamed, Mohamed-Said Naït-Saïd, and Nasreddine Nait-Said. "Incipient Inter-Turn Short Circuit Fault Estimation Based on a Faulty Model Observer and ANN-Method for Induction Motor Drives." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 12, no. 4 (August 23, 2019): 374–83. http://dx.doi.org/10.2174/2352096511666180705113021.
Повний текст джерелаДисертації з теми "Stator short circuit faults"
Arkan, Muslum. "Stator fault diagnosis in induction motors." Thesis, University of Sussex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310244.
Повний текст джерелаBabu, Hareesh. "Finite-element analysis of an induction motor with inter-turn short-circuit faults." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-290082.
Повний текст джерелаKortslutning mellan varven i en asynkronmotors statorlindning (ITSC) är en av de vanligaste källorna för fel som påverkar dess drifttillförlitlighet. I detta examensarbete utvecklas en finit-element (FE) modell för att studera ITSC- fel. FE-modellen är utvecklad för en asynkronmotorprototyp som kan emulera ITSC-fel. Med den utvecklade modellen utförs en simuleringsstudie för att förstå beteendet hos olika elektriska och magnetiska egenskaper både i tids- och frekvensdomän. Dessa egenskaper är goda indikatorer av statorlindningsfel och kan därför med fördel användas i ett tillståndsövervakningssystem. Prototypmaskinen har testats experimentellt och de erhållna resultaten jämförs med FE-simuleringen och analysresultaten. Det analytiska resultatet, FEM- simuleringarna och den experimentella utvärderingen uppvisade god överrensstämmelse vad gäller felströmmen. Dock finns det en mindre avvikelse när det gäller amplituden hos statorströmmens negativa fasföljd. Orsaken till denna avvikelse är att prototypmaskinens geometri inte är helt känd.
Singh, Bhanu Pratap. "Real-time detection of stator resistance unbalances in three phase drives." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-286813.
Повний текст джерелаUppskattningsvis 30% av alla fel i induktionsmaskiner (IM) är kopplad till dess stator. Dessa fel är i huvudsak Inter-Turn Short Circuit (ITSC)-fel, dvs. två lindningar inom IM:ens stator blir kortsluta pga. ett isoleringsfel. Emellertid kan man undvika ITSC-fel genom att detektera dem i förhand och planera underhåll. Det här examensarbetet undersöker två metoder för att detektera ett förestående ITSC-fel i en tre-fas IM. Den första metoden är baserad på asymmetrin i IM:er pga. ITSC-felet. Resultatet av den här asymmetrin är att en negativ sekvens genereras i IM:ens statorspänning och statorström. En oskadad IM kan också visa dessa negativa sekvenser pga. tillverksprocessen och statorspänningsobalanser. Egenskaperna och kompensationsmetoderna för dessa negativa sekvenser i en oskadad IM kommer att diskuteras. Resultaten visar att efter kompenseringen av de negativa sekvenserna i en oskadad IM, kan de användas för att detektera ITSC-fel och efteråt för att beräkna felstorheter och även statormotståndobalanser. Den andra metoden för att detektera ITSC-fel är baserad på en undersökning av statormotståndobalanser. Ett tre-fas-drivsystem används för att injektera likspänning i den stationära referensramen. Likströmmen som följer av denna likspänning mäts och statorfasmotstånden beräkna efteråt med Ohms lag. I en oskadad IM är fasmotstånden balanserade. Däremot, när ett ITSC-fel uppstår i en fas, avviker fasmotståndet i den felaktiga fasen från de andra två fasernas, vilket kan användas för att detektera ITSC-fel.
Filleau, Clément. "Mise en place d'une méthodologie de modélisation en vue du diagnostic des défauts électriques des alternateurs." Phd thesis, Toulouse, INPT, 2017. http://oatao.univ-toulouse.fr/19288/1/Filleau.pdf.
Повний текст джерелаIsaac, Leslie Thomas. "Puffer circuit breaker diagnostics using novel optical fibre sensors." Thesis, University of Liverpool, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263762.
Повний текст джерелаOliveira, Ãtila GirÃo de. "Neural classifier aplied in stator winding inter-turn short circuit in three-phase induction motors driven by frequency converter." Universidade Federal do CearÃ, 2014. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12285.
Повний текст джерелаThis dissertation reports applications of artificial neural networks to detect stator winding interturn fault of three phase induction motor drived by frequency inverter. The artificial neural networks, like Simple and Multilayer Perceptron, served as off-line classifiers to short-circuit fault condition or healthy condition. In the training of Multilayer Perceptron, two different algorithms are used: the error back-propagation, which is a classic algorithm, and the extreme learning machine, as a relative new alternative for the classic back-propagation. The new one is more worthwhile because of its implementation easiness and higher speed of computation. The database used on the training and validation of the networks is created from an experimental setting, therefore it is composed by true data. The attributes used as failuresâ indicators are selected from certain frequencies of the spectrum, based on some theories of current signature analysis. In the second instance, the technique of principal components analysis is employed. The results obtained for the designed classifiers are shown, and some considerations are made on their use in real time embedded applications, which is the most important projection for future researches.
Este trabalho deriva da aplicaÃÃo de redes neurais artificiais para a detecÃÃo de curto-circuito entre espiras em motor de induÃÃo trifÃsico, acionado por inversor de frequÃncia. As redes neurais artificiais, do tipo Perceptron Simples e Multicamadas, sÃo usadas para detectar falhas de curto-circuito no bobinamento estatÃrico de motores de induÃÃo trifÃsicos de forma off-line. Para treinamento do Perceptron Multicamadas sÃo usados dois algoritmos distintos: o error back-propagation, que figura como o algoritmo clÃssico na literatura especializada, e o extreme learning machine, que à uma alternativa, relativamente recente, ao algoritmo clÃssico. Este algoritmo à uma opÃÃo atraente para o desenvolvimento rÃpido de classificadores. O banco de dados usado para treinamento e validaÃÃo das redes à obtido a partir de experimentaÃÃo laboratorial, portanto composto de dados reais. Os atributos utilizados para a detecÃÃo da falha sÃo componentes de frequÃncia do espectro harmÃnico da corrente estatÃrica do motor. O critÃrio de escolha destas componentes, a priori, à fundamentado em resultados de investigaÃÃes prÃvias da assinatura de corrente e, em segunda instÃncia, à aplicada a tÃcnica de anÃlise de componentes principais. SÃo apresentados os resultados obtidospelos classificadores projetados, e feitas algumas consideraÃÃes quanto à utilizaÃÃo destes em aplicaÃÃo embarcada e em tempo real, que à a principal projeÃÃo de futuros trabalhos a partir do atual.
Martins, João Roberto Deroco. "Detecção e classificação de curto-circuitos em sistemas de distribuição usando rede neural artificial ARTMAP nebulosa /." Ilha Solteira : [s.n.], 2010. http://hdl.handle.net/11449/87047.
Повний текст джерелаBanca: Anna Diva Plasencia Lotufo
Banca: Marco Aparecido Queiroz Duarte
Resumo: Este trabalho apresenta uma metodologia para detecção e classificação de faltas do tipo curto-circuito. Esta operação de diagnóstico tem como principal operador um banco de redes neurais artificiais (RNAs) do tipo ARTMAP Nebulosa. Tal ferramenta segue a principal filosofia das RNAs: o reconhecimento de padrões, através de um trei- namento supervisionado inicial, responsável por atualizar os parâmetros das redes con- comitantemente com os resultados desejados. Finalizada a fase de adaptação, as redes serão capazes de, após receber novos padrões, classificá-los, de forma a propiciar, ao operador, informações importantes quanto ao estado de transmissão de barras presentes em um determinado complexo elétrico. Aqui, tomou-se como modelo a simulação de um grande alimentador real, composto por mais de 800 barras. Aliados às RNAs, tam- bém foram aplicadas, no que se refere à análise de dados amostrados de corrente elétri- ca, duas importantes e flexíveis ferramentas matemáticas: a Transformada de Fourier e a Transformada Wavelet. .Observa-se, ao final do trabalho, que os resultados apresenta- dos são bastante encorajadores, o que possibilitaria a utilização do programa em um ambiente real
Abstract: This work presents a detection and classification of short-circuit faults metho- dology. The main operator of this diagnostic operation is a Fuzzy ARTMAP Artificial Neural Networks (ANN) bank. This tool follows the ANN's main core: pattern recogni- tion, through an initial supervised training stage, responsible for updating the parame- ters of the networks con-comitant with the desired results. Completed the adaptation phase, the network will be able to, after receiving new standards, classifying them in order to provide to the operator important information about the state of transmission of bars present in a given complex electric. Here, there is, like a model, a simulation of a real big feeder, comprising more than 800 bars. Besides the ANNs, two important and flexible mathematical tools were also applied with regard to the analysis of sampled data of electric current: Fourier Transform and Wavelet Transform. At the end of the work the results presented are very encouraging, which would allow the use of the pro- gram in a no simulations real environment
Mestre
Bernardes, Haislan Ranelli Santana. "Detecção e classificação de faltas em sistemas de distribuição de energia elétrica usando a análise multirresolução e a rede neural artificial ARTMAP-fuzzy /." Ilha Solteira, 2019. http://hdl.handle.net/11449/183118.
Повний текст джерелаResumo: Esta pesquisa apresenta o desenvolvimento de uma ferramenta para a detecção e classificação de curtos-circuitos em sistemas de distribuição de energia elétrica, a qual é baseada no uso combinado da análise multirresolução e rede neural ARTMAP-fuzzy. A análise multirresolução permite a identificação de singularidades nas oscilografias e a rede da família ART garante ao sistema classificador a capacidade de aprendizado contínuo de novos padrões sem perder o conhecimento previamente adquirido. Todo o processo de diagnóstico é realizado em uma única etapa, reduzindo o custo computacional da metodologia. A eficiência do sistema é verificada por uma análise direta, na qual se contabiliza a quantidade total de acertos, e por uma avaliação comparativa, a qual envolve a substituição da rede ARTMAP-fuzzy pela rede ARTMAP-Euclideana. Resultados mostram que o sistema é eficiente, sendo capaz de detectar e classificar 100% das falhas elétricas.
Abstract: This research presents the development of a tool for the detection and classification of short circuits in electric power distribution systems, which is based on the combined use of multi-resolution analysis and fuzzy ARTMAP neural network. The multiresolution analysis allows the identification of singularities in the oscillographs and the ART family network guarantees to the classifier the ability to continuously learn new patterns without losing the previously acquired knowledge. The entire diagnostic process is performed in a single step, reducing the computational effort. The efficiency of the system is verified by a direct analysis, in which the total number of hits is counted, and by a comparative evaluation, which involves the replacement of the fuzzy ARTMAP network by the Euclidean ARTMAP network. Results show that the system is efficient, being able to detect and classify 100% of the electrical faults.
Mestre
Martins, João Roberto Deroco [UNESP]. "Detecção e classificação de curto-circuitos em sistemas de distribuição usando rede neural artificial ARTMAP nebulosa." Universidade Estadual Paulista (UNESP), 2010. http://hdl.handle.net/11449/87047.
Повний текст джерелаCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Este trabalho apresenta uma metodologia para detecção e classificação de faltas do tipo curto-circuito. Esta operação de diagnóstico tem como principal operador um banco de redes neurais artificiais (RNAs) do tipo ARTMAP Nebulosa. Tal ferramenta segue a principal filosofia das RNAs: o reconhecimento de padrões, através de um trei- namento supervisionado inicial, responsável por atualizar os parâmetros das redes con- comitantemente com os resultados desejados. Finalizada a fase de adaptação, as redes serão capazes de, após receber novos padrões, classificá-los, de forma a propiciar, ao operador, informações importantes quanto ao estado de transmissão de barras presentes em um determinado complexo elétrico. Aqui, tomou-se como modelo a simulação de um grande alimentador real, composto por mais de 800 barras. Aliados às RNAs, tam- bém foram aplicadas, no que se refere à análise de dados amostrados de corrente elétri- ca, duas importantes e flexíveis ferramentas matemáticas: a Transformada de Fourier e a Transformada Wavelet. .Observa-se, ao final do trabalho, que os resultados apresenta- dos são bastante encorajadores, o que possibilitaria a utilização do programa em um ambiente real
This work presents a detection and classification of short-circuit faults metho- dology. The main operator of this diagnostic operation is a Fuzzy ARTMAP Artificial Neural Networks (ANN) bank. This tool follows the ANN’s main core: pattern recogni- tion, through an initial supervised training stage, responsible for updating the parame- ters of the networks con-comitant with the desired results. Completed the adaptation phase, the network will be able to, after receiving new standards, classifying them in order to provide to the operator important information about the state of transmission of bars present in a given complex electric. Here, there is, like a model, a simulation of a real big feeder, comprising more than 800 bars. Besides the ANNs, two important and flexible mathematical tools were also applied with regard to the analysis of sampled data of electric current: Fourier Transform and Wavelet Transform. At the end of the work the results presented are very encouraging, which would allow the use of the pro- gram in a no simulations real environment
Otava, Lukáš. "Algoritmy monitorování a diagnostiky pohonů se synchronními motory." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-447552.
Повний текст джерелаКниги з теми "Stator short circuit faults"
Brown, John C. An investigation into short circuit faults on the power supply of D.C.traction systems. Birmingham: University of Birmingham, 1988.
Знайти повний текст джерелаEvans, R. W. Test report--fault current through graphite filament reinforced plastic: Under contract NAS8-39983. Marshall Space Flight Center, Ala: National Aeronautics and Space Administration, [George C. Marshall Space Flight Center, 1997.
Знайти повний текст джерелаDiagnostics of Electrical Equipment Faults and Power Overhead Transmission Line Condition by Monitoring Systems: Short-Circuit Testing of Power Transformers. Nova Science Publishers, Incorporated, 2016.
Знайти повний текст джерелаGeorge C. Marshall Space Flight Center., ed. Test report--fault current through graphite filament reinforced plastic: Under contract NAS8-39983. Marshall Space Flight Center, Ala: National Aeronautics and Space Administration, [George C. Marshall Space Flight Center, 1997.
Знайти повний текст джерелаGeorge C. Marshall Space Flight Center., ed. Test report--fault current through graphite filament reinforced plastic: Under contract NAS8-39983. Marshall Space Flight Center, Ala: National Aeronautics and Space Administration, [George C. Marshall Space Flight Center, 1997.
Знайти повний текст джерелаGeorge C. Marshall Space Flight Center., ed. Test report--fault current through graphite filament reinforced plastic: Under contract NAS8-39983. Marshall Space Flight Center, Ala: National Aeronautics and Space Administration, [George C. Marshall Space Flight Center, 1997.
Знайти повний текст джерелаIEEE Power Engineering Society. Switchgear Committee., ed. Supplement to IEEE guide for synthetic fault testing of AC high-voltage circuit breakers rated on a symmetrical current basis: 8.3.2, recovery voltage for terminal faults, asymmetrical short-circuit current. New York: IEEE, 1998.
Знайти повний текст джерелаЧастини книг з теми "Stator short circuit faults"
dos Santos, Tiago, Fernando J. T. E. Ferreira, João Moura Pires, and Carlos Viegas Damásio. "Severity Estimation of Stator Winding Short-Circuit Faults Using Cubist." In Progress in Artificial Intelligence, 217–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65340-2_18.
Повний текст джерелаXiangli, Kang, Ruiqing Ma, Qingchao Zhang, and Wei Wang. "Modeling and Simulation of Short Circuit Faults in Stator Coils of Brushless DC Motor." In Lecture Notes in Electrical Engineering, 35–45. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01273-5_4.
Повний текст джерелаYoung-Jin, Goh, and Kim Kyoung-Min. "Diagnosis of Stator Fault by Inter-Turn Short Circuit for Three-Phase Induction Motor." In Advances in Intelligent Systems and Computing, 609–18. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1165-9_56.
Повний текст джерелаLi, Junqing, Dong Wang, Ximei Wang, and Lipeng Zhang. "Fault Features Study of Doubly Fed Induction Generators on the Stator Windings Turn-to-Turn Short Circuit." In Proceedings of the Second International Conference on Mechatronics and Automatic Control, 29–38. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13707-0_4.
Повний текст джерелаLi, Junqing, Haibo Yu, and Lipeng Zhang. "Application of Ensemble Empirical Mode Decomposition on Stator Inter-turn Short-Circuit Fault in Doubly Fed Induction Generators." In Proceedings of the Second International Conference on Mechatronics and Automatic Control, 73–83. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13707-0_9.
Повний текст джерелаThomson, William T. "Critical Appraisal of Mcsa to Diagnose Short Circuited Turns in LV and HV Stator Windings and Faults in Roller Element Bearings in SCIMS." In Current Signature Analysis for Condition Monitoring of Cage Induction Motors, 359–73. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119175476.ch12.
Повний текст джерелаSziray, József. "Test Generation for Short-Circuit Faults in Digital Circuits." In Studies in Computational Intelligence, 313–19. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03206-1_21.
Повний текст джерелаHu, Guozhao, Xixiu Wu, Fei Long, and Shipu Wu. "A 3D-Coupled Field-Circuit Model for Analyzing the Internal Short-Circuit Faults of Power Transformer." In Proceedings of the Second International Conference on Mechatronics and Automatic Control, 55–64. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13707-0_7.
Повний текст джерелаRajamany, Gayatridevi, and Sekar Srinivasan. "Neural Network Approach for Inter-turn Short-Circuit Detection in Induction Motor Stator Winding." In Advances in Intelligent Systems and Computing, 537–50. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7868-2_52.
Повний текст джерелаPires, Yomara, Jefferson Morais, Claudomir Cardoso, and Aldebaro Klautau. "Data Mining Applied to the Electric Power Industry: Classification of Short-Circuit Faults in Transmission Lines." In Innovative Applications in Data Mining, 107–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88045-5_6.
Повний текст джерелаТези доповідей конференцій з теми "Stator short circuit faults"
Yihan Zhao, Yu Chen, Lulu Wang, Attiq Ur Rehman, Yonghong Yin, Yonghong Cheng, and Toshikatsu Tanaka. "Experiment research and analysis of stator winding short circuit faults in DFIG." In 2016 International Conference on Condition Monitoring and Diagnosis (CMD). IEEE, 2016. http://dx.doi.org/10.1109/cmd.2016.7757775.
Повний текст джерелаWan, Shuting, and Yonggang Li. "Vibration Fault Diagnosis Method Based on Compositive Characteristics of Rotor Vibration and Stator Current." In ASME 2007 Power Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/power2007-22011.
Повний текст джерелаEbrahimi, Saeed Hasan, Martin Choux, and Van Khang Huynh. "Modeling Stator Winding Inter-Turn Short Circuit Faults in PMSMs including Cross Effects." In 2020 International Conference on Electrical Machines (ICEM). IEEE, 2020. http://dx.doi.org/10.1109/icem49940.2020.9270890.
Повний текст джерелаLebaroud., A., and G. Clerc. "Analysis of stator short-circuit faults for induction machine using finite element modeling." In 2010 7th International Multi-Conference on Systems, Signals and Devices (SSD). IEEE, 2010. http://dx.doi.org/10.1109/ssd.2010.5585589.
Повний текст джерелаNiu, Jialin, Zehui Mao, Yufeng Zhang, Bin Jiang, and Yongliang Guo. "Observer Based Fault Estimation for Induction Motor with Stator Inter-turn Short Circuit Faults and Disturbances." In 2019 Chinese Control Conference (CCC). IEEE, 2019. http://dx.doi.org/10.23919/chicc.2019.8866487.
Повний текст джерелаHe, Jiangbiao, Chad Somogyi, Andrew Strandt, and Nabeel A. O. Demerdash. "Diagnosis of stator winding short-circuit faults in an interior permanent magnet synchronous machine." In 2014 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2014. http://dx.doi.org/10.1109/ecce.2014.6953825.
Повний текст джерелаKhov, Makara, Jeremi Regnier, and Jean Faucher. "Detection of turn short-circuit faults in stator of PMSM by on-line parameter estimation." In 2008 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM). IEEE, 2008. http://dx.doi.org/10.1109/speedham.2008.4581092.
Повний текст джерелаChen, Peng, Ying Xie, and Shengming Hu. "The Effect of Stator Inter-Turn Short Circuit Faults on Electromagnetic Performances of Induction Motors." In 2019 22nd International Conference on Electrical Machines and Systems (ICEMS). IEEE, 2019. http://dx.doi.org/10.1109/icems.2019.8921850.
Повний текст джерелаSayed-Ahmed, Ahmed, Chia-chou Yeh, Nabeel O. Demerdash, and Behrooz Mirafzal. "Analysis of Stator Winding Inter-Turn Short-Circuit Faults in Induction Machines for Identification of the Faulty Phase." In Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting. IEEE, 2006. http://dx.doi.org/10.1109/ias.2006.256731.
Повний текст джерелаYuchechen, Guillermo D., Manuel A. Mazzoletti, and Guillermo R. Bossio. "Effects of Stator Winding Interturn Short-Circuit Faults of the IM by Using Intantaneous Power Theory." In 2018 Argentine Conference on Automatic Control (AADECA). IEEE, 2018. http://dx.doi.org/10.23919/aadeca.2018.8577392.
Повний текст джерелаЗвіти організацій з теми "Stator short circuit faults"
Masrur, M. A., ZhiHang Chen, and Yi L. Murphey. Intelligent Diagnosis of Open and Short Circuit Faults in Electric Drive Inverters For Real-Time Applications. Fort Belvoir, VA: Defense Technical Information Center, March 2009. http://dx.doi.org/10.21236/ada513126.
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