Relevant bibliographies by topics / Winding interturn short-circuit

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Winding interturn short-circuit'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Winding interturn short-circuit"

1

Mustafayev, Rauf, Diyar Akhmedov, and Aslan Akhmedov. "Diagnosis of Asynchronous Motor with Inter Connective Circuit in Stator Winding." Известия высших учебных заведений. Электромеханика 64, no. 1 (2021): 48–53. http://dx.doi.org/10.17213/0136-3360-2021-1-48-53.

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The problems of applying the achievement of general technical diagnostics for the recognition and assessment of the technical state of the stator winding in the process of performing functional processes by an asynchronous motor are considered. It is proposed to use the informative parameters of vibration acceleration obtained from full-scale experiments carried out in idle and load modes of an asynchronous motor for diagnosing an intertuеrn short circuit that often occurs in the stator winding. It is shown that for recognizing a malfunction of the stator winding of an induction motor, mathematical methods of technical diagnostics are effective, in particular, the method of potential functions and the method of diagnostics based on the angular distance in the feature space. The sequence of methods, rapid assessment of the technical condition of the stator winding and the determination of the interturn short circuit at the initial stages of its occurrence during the operation of the induction motor is given.
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Yang, Zhongyi, and Yiguang Chen. "Interturn Short-Circuit Fault Detection of a Five-Phase Permanent Magnet Synchronous Motor." Energies 14, no. 2 (2021): 434. http://dx.doi.org/10.3390/en14020434.

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Interturn short circuits are a common fault of permanent magnet synchronous motors (PMSMs). This paper proposes a new method to detect the interturn short-circuit fault (ISCF) of a five-phase PMSM. The method first takes the command voltage and measured current of each phase winding as the original signal and then obtains the delay signal orthogonal to the original signal via Hilbert transform. Then, the generalized instantaneous reactive power of each phase can be calculated from the orthogonal voltage and current signals of each phase. Finally, the influence of the ISCF on the generalized instantaneous reactive power of each phase is analyzed under different working conditions. By comparing the difference in the generalized instantaneous reactive power of each phase, it can be determined which phase winding has the ISCF. The proposed method is verified by simulated and experimental results.
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Rajamany, Gayatridevi, Sekar Srinivasan, Krishnan Rajamany, and Ramesh K. Natarajan. "Induction Motor Stator Interturn Short Circuit Fault Detection in Accordance with Line Current Sequence Components Using Artificial Neural Network." Journal of Electrical and Computer Engineering 2019 (December 11, 2019): 1–11. http://dx.doi.org/10.1155/2019/4825787.

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The intention of fault detection is to detect the fault at the beginning stage and shut off the machine immediately to avoid motor failure due to the large fault current. In this work, an online fault diagnosis of stator interturn fault of a three-phase induction motor based on the concept of symmetrical components is presented. A mathematical model of an induction motor with turn fault is developed to interpret machine performance under fault. A Simulink model of a three-phase induction motor with stator interturn fault is created for extraction of sequence components of current and voltage. The negative sequence current can provide a decisive and rapid monitoring technique to detect stator interturn short circuit fault of the induction motor. The per unit change in negative sequence current with positive sequence current is the main fault indicator which is imported to neural network architecture. The output of the feedforward backpropagation neural network classifies the short circuit fault level of stator winding.
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Yucai, Wu, and Li Yonggang. "Diagnosis of Rotor Winding Interturn Short-Circuit in Turbine Generators Using Virtual Power." IEEE Transactions on Energy Conversion 30, no. 1 (2015): 183–88. http://dx.doi.org/10.1109/tec.2014.2339300.

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Quan, Yu Sheng, Zong Cheng Zhang, Guang Chen, and Dai Juan Wang. "Research on Detection Method of Transformer Interturn Short Circuit Based on Wavelet Analysis." Applied Mechanics and Materials 521 (February 2014): 358–61. http://dx.doi.org/10.4028/www.scientific.net/amm.521.358.

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Distribution transformer is an important device in the power supply system, once its failure can cause power outages. According to statistics, 70% -80% of the transformer accident was caused by a short circuit between the transformer turns. Based on the large number of experimental data analysis and processing, a new inter-turn short circuit transformer diagnostic methods is proposed. In this paper, the ground current of transformer core as the signal source, Using wavelet multi-resolution technology the signal wavelet multiscale decomposition, the decomposition of different signals of the same scale, get the high frequency components of the signal, achieve short-circuit fault diagnosis between transformer winding turns by comparing the number of the high-frequency component contained in different signals in the decomposition of the same scale. To illustrate the effectiveness of the method, the paper through a series of experiments and data processing, verify the effectiveness and feasibility of the method.
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Tang, Gui-Ji, Hong-Chun Jiang, Yu-Ling He, and Qing-Fa Meng. "Electromagnetic Forces and Mechanical Responses of Stator Windings before and after Rotor Interturn Short Circuit in Synchronous Generators." Mathematical Problems in Engineering 2020 (December 30, 2020): 1–19. http://dx.doi.org/10.1155/2020/5892312.

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This paper studies the stator winding electromagnetic force behaviors before and after rotor inter-turn short circuit (RISC) in synchronous generator. Different from other studies, this paper not only studies the electromagnetic force characteristics, but also investigates the mechanical responses, the damage regularity, and the countermeasure of the stator winding. Firstly, formulas of electromagnetic force online and end part are obtained. Then, a 3D finite element model of a 3-pair-pole simulation generator is applied to get the electromagnetic force, and the dangerous stator slot is found. Finally, the mechanical response of each end winding is acquired, and especially the directional deformations of nose part are calculated. It shows that the occurrence of RISC will bring in times of rotor rotating frequency components to electromagnetic force, but the DC component and 2p times of rotor rotating frequency components are still the main that will be decreased. Additionally, the winding insulation wear in the same layer is more serious than that in a different layer, nose fatigue fracture begins with the center, and nose insulation wear starts from the top.
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Ma, Minghan, Yonggang Li, Yucai Wu, and Chenchen Dong. "Multifield Calculation and Analysis of Excitation Winding Interturn Short Circuit Fault in Turbo-Generator." Energies 11, no. 10 (2018): 2626. http://dx.doi.org/10.3390/en11102626.

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Excitation winding interturn short circuit (EWISC) is a common fault in turbo-generators. Once the fault occurs, if not handled in time, it will result in significant security risks to the power system. Using the multifield characteristics of fault generators for a comprehensive diagnosis can make the diagnostic results more accurate and credible. In this paper, taking a TA-1100-78 type, two pole pairs turbo-generator as the research object, the two-dimensional finite element electromagnetic model of stator/rotor and the three-dimensional finite element heat transfer model of rotor were established. The electromagnetic field, temperature field, and stress field of the generator were simulated and analyzed. At the same time, the air gap magnetic field, three-dimensional temperature field, and stress field distribution of the rotor were calculated for EWISC faults in different fault degrees and positions. The results showed that the EWISC fault weakened the air gap magnetic field and caused unbalanced electromagnetic distribution. At the same time, it caused a distortion of the rotor temperature field, resulting in an unbalanced distribution of the temperature field. The stress field was affected by the distortion of temperature field, and the local thermal stress increased but did not exceed the yield limit of the material. Restorable elastic deformation occurred when the rotor was heated, which caused the thermal bending of the rotor. The method adopted in this paper can provide a reference for the calculation of multiphysical field after a generator fault. It is also pointed out that the thermal unbalance influence should not be neglected in the study of generator vibration characteristics.
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Dolgih, Roman, Ivan Suvorov, George Palkin, Sergey Kakaurov, and Marina Morozova. "Development of the software-hardware complex for diagnostics of inter-turn short circuits of stator windings of asynchronous motors." E3S Web of Conferences 288 (2021): 01040. http://dx.doi.org/10.1051/e3sconf/202128801040.

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Up to 38% of asynchronous motor (AM) failures are caused by damage to the stator insulation. Despite the wide variety of methods, the reliability of determining the inter-turn short circuits of stator windings under operating voltage still remains at a low level. The existing methods for diagnostics of asynchronous motor failure of the interturn short circuit of stator winding have been examined. New diagnostic methods for individual parameters developed in the course of the previous study are described. A new diagnostic method is formulated, on the basis of which the research work is carried out. The method will allow us to constantly monitor the technical condition of the stator winding, and identify its damage at an early stage of their development. Diagnostics can be performed without dismantling the engine and without removing it from the working process. The microprocessor unit is implemented for diagnostics of the technical condition of AM introducing this method. Moreover, the software and hardware complex is implemented for diagnostics of the technical condition for AM. The results of experiments on a laboratory stand with inter-turn AM closures are presented, which confirm the higher reliability of monitoring.
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Arumugam, Puvan, Tahar Hamiti, and Chris Gerada. "Modeling of Different Winding Configurations for Fault-Tolerant Permanent Magnet Machines to Restrain Interturn Short-Circuit Current." IEEE Transactions on Energy Conversion 27, no. 2 (2012): 351–61. http://dx.doi.org/10.1109/tec.2012.2188138.

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Fan, Ying, Chenxue Li, Weixia Zhu, Xiangyang Zhang, Li Zhang, and Ming Cheng. "Stator Winding Interturn Short-Circuit Faults Severity Detection Controlled by OW-SVPWM Without CMV of a Five-Phase FTFSCW-IPM." IEEE Transactions on Industry Applications 53, no. 1 (2017): 194–202. http://dx.doi.org/10.1109/tia.2016.2609848.

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Dissertations / Theses on the topic "Winding interturn short-circuit"

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Oliveira, 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.

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CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior<br>This 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.<br>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.
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Conference papers on the topic "Winding interturn short-circuit"

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Li, Junqing, Weiming Shi, and Qiujia Li. "Research on interturn short circuit fault location of rotor winding in synchronous electric machines." In 2017 20th International Conference on Electrical Machines and Systems (ICEMS). IEEE, 2017. http://dx.doi.org/10.1109/icems.2017.8056040.

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Zheng An Ping, Yang Juan, and Wang Ling. "Fault Detection of Stator Winding Interturn Short Circuit in PMSM Based on Wavelet Packet Analysis." In 2013 Fifth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2013). IEEE, 2013. http://dx.doi.org/10.1109/icmtma.2013.141.

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Zhong, Hao, Yuling He, Guiji Tang, Yuchao Meng, and Weiqi Deng. "Analysis on exciting winding electromagnetic force of Turbo-generator under rotor interturn short circuit fault." In 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016). Atlantis Press, 2016. http://dx.doi.org/10.2991/aest-16.2016.67.

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Yuchechen, 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.

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Tong Liu, Jin Huang, and Jiaqiang Yang. "Diagnostic Method of Induction Motor Stator Winding Interturn Short Circuit Fault Based on the Feature Impedance." In 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1714170.

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Yan, Decheng, Tunan Shen, Ahmet Kilic, and Hans-Christian Reuss. "New Fault Detection Method for Interturn Short Circuit on Stator Winding of IPMSM for Highly Automated Driving Applications." In 2019 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2019. http://dx.doi.org/10.1109/sii.2019.8700411.

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Oliveira, Atila Girao de, Ricardo Silva The Pontes, and Claudio Marques de Sa Medeiros. "Neural Network Used to Stator Winding Interturn Short-Circuit Fault Detection in an Induction Motor Driven by Frequency Converter." In 2013 BRICS Congress on Computational Intelligence & 11th Brazilian Congress on Computational Intelligence (BRICS-CCI & CBIC). IEEE, 2013. http://dx.doi.org/10.1109/brics-cci-cbic.2013.82.

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Li, Tianhui, Boyan Jia, Bin Ding, et al. "Simulation Study on Interturn Short Circuit of Rotor Windings in Generator by RSO Method." In 2018 IEEE International Conference on High Voltage Engineering and Application (ICHVE). IEEE, 2018. http://dx.doi.org/10.1109/ichve.2018.8641917.

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Iamamura, B. A. T., Y. Le Menach, A. Tounzi, N. Sadowski, and E. Guillot. "Study of interturn short circuit in rotor windings of a synchronous generator using FEM." In 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation (CEFC 2010). IEEE, 2010. http://dx.doi.org/10.1109/cefc.2010.5481857.

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Mazzoletti, Manuel A., Guillermo R. Bossio, and Cristian H. De Angelo. "A strategy for interturn short-circuit fault detection in PMSM with partitioned stator windings." In 2017 XVII Workshop on Information Processing and Control (RPIC). IEEE, 2017. http://dx.doi.org/10.23919/rpic.2017.8214325.

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