Relevant bibliographies by topics / Stator short circuit faults

Academic literature on the topic 'Stator short circuit faults'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Stator short circuit faults"

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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.

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Stator winding inter turn short-circuit fault is one of the most common internal faults of fault-tolerant machine, which can disconnect the fault phases and keep operating correctly in the event of a failure. Stator winding short-circuit fault model is established through analysis. Based on finite element method, the high-power density fault-tolerant machine internal magnetic field simulation and analysis is implemented using Maxwell2D and induced voltage frequency spectrum is analyzed by FFT method. The characteristics of stator winding short-circuit faults are summarized, which lay a solid foundation for fault-tolerant machine earlier faults prediction and winding switching.
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Aubert, 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.

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<p class="Abstract">This paper deals with an Extended Kalman Filter based fault detection for inter-turn short-circuit in Permanent Magnet Synchronous Generators. Inter-turn short-circuits are among the most critical faults in the PMSG. Indeed, due to permanent magnets, the short-circuit current is maintained as long as the machine is rotating. Thus, a specific faulty model in d-q frame is developed to estimate the number of short-circuited turns which are used to build a fault indicator. Simulation results demonstrate the sensitivity and the robustness of the proposed fault indicator against various operation points on an electrical network even for a few number of short-circuited turns.</p>
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Liang, 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.

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The stator inter-turn short circuit fault is one of the most common and key faults in permanent magnet synchronous motor (PMSM). This paper introduces a time–frequency method for inter-turn fault detection in stator winding of PMSM using improved wavelet packet transform. Both stator current signal and vibration signal are used for the detection of short circuit faults. Two different experimental data from a three-phase PMSM were processed and analyzed by this time–frequency method in LabVIEW. The feasibility of this approach is shown by the experimental test.
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Tang, 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.

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The modeling of stator and rotor faults is the basis of the development of online monitoring techniques. To obtain reliable stator and rotor fault models, this paper focuses on dynamic modeling of the stator and rotor faults in real-time, which adopts a multiple-coupled-circuit method by using a winding function approach for inductance calculation. Firstly, the model of the induction machine with a healthy cage is introduced, where a rotor mesh that consists of a few rotor loops and an end ring loop is considered. Then, the stator inter-turn fault model is presented by adding an extra branch with short circuit resistance on the fault part of a stator phase winding. The broken rotor bar fault is then detailed by merging and removing the broken-bar-related loops. Finally, the discrete models under healthy and faulty conditions are developed by using the Tustin transformation for digital implementation. Moreover, the stator and rotor mutual inductances are derived as a function of the rotor position according to the turn and winding functions distribution. Simulations and experiments are performed on a 2.2-kW/380-V/50-Hz three-phase and four-pole induction motor to show the performance of the stator and rotor faults, where the saturation effect is considered in simulations by exploiting the measurements of a no load test. The simulation results are in close agreement with the experimental results. Furthermore, magnitudes of the characteristic frequencies of 2f1 in torque and (1 ± 2s)f1 in current are analyzed to evaluate the stator and rotor fault severity. Both indicate that the stator fault severity is related to the short circuit resistance. Further, the number of shorted turns and the number of continuous broken bars determines the rotor fault severity.
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Alawady, 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.

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<p>The paper presents the description for diagnostic methods of induction motor's stator windings fault. The presented methods use Frequency Response Analysis (FRA) technique for detection of Winding Faults in Induction Motor . This method is previously reliable method for faults diagnosis and detection in many parts of transformers including transformer windings. In this paper, this method was used for motor windings faults detection. This paper presents the FRA response interpretation on internal short circuit (SC) fault at stator winding on three cases studies of different three-phase induction motors (TPIM), were analysed according to two status: healthy induction motor at normal winding status and same motor with windings shorted of main windings. A conclusion of this paper provides the interpretation of and validation the FRA response due to internal SC fault case by using NCEPRI algorithm, which is considered as one of certified statistical indicators. The proposed method in this paper had a useful result for detect and diagnosis of stator windings faults of TPIM. The applications of developed method can be used to detece the other machines types faults.</p>
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Puzakov, Andrey. "Diagnosing of automotive alternators on thermal state." MATEC Web of Conferences 298 (2019): 00005. http://dx.doi.org/10.1051/matecconf/201929800005.

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Since automotive alternators serve as the primary sources of power onboard of vehicles, the online diagnostics of technical conditions thereof is a relevant task. An advantage of temperature as a diagnostic parameter is sensitivity to most faults at the early stage of their development. Physical modeling of faults (stator one-line open fault, stator turn-to-turn short circuit, stator winding phase-to-phase short circuit, circuit opening and short circuit of rectifier diodes) has been done by forced increase (decrease) of electrical resistance between alternator elements. In order to measure alternator temperature, it has been brought to steady thermal state within 20 minutes. It has been found that the alternator temperature in case of faults can increase the rated temperature by 10-30 °С even when the alternator operates without load. An algorithm has been developed to find alternator faults by evaluating the thermal state thereof, which can become a basis of an onboard automatic online diagnosing system of an automotive alternator.
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Głowacz, 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.

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This paper describes detection of synchronous motor inter-turn faults based on symptoms contained in stator phase currents. Armature short circuit, caused by insulation degradation are quite commonly occurring defects in electrical machines. Initially, short circuit comprises mostly single coils, causing the temperature rise due to higher value of current, which can reach up to tens times of the rated value. At the same time the phase current does not increase significantly. Increased temperature leads to rapid damage of the insulation and shorting the adjacent coils spreading the fault to the entire winding in a short time. Thus, it is very important to detected this type of fault in its early stage. Unfortunately currently used motor protection devices are insensitive to short-circuits of a small number of turns, because they cause too small quantitative changes in the phase currents. Phase currents begin to rise to the level detectable by protection devices when a large part of the winding is already covered by a fault. Therefore, there is a need for research on diagnostics of this type of damage. For the purpose of this paper a stepped short circuit fault of one coil group in the stator phase winding is performed. Shorting resistance values are chosen so that the short fault is diagnosed in its early stage. Spectral analysis of stator phase currents is carried out followed by spectral analysis of stator currents Park’s vector. Comparison of the results of both studies shows that the signal of stator current Park’s vector is more suitable in diagnostics of this type of faults.
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Fadzail, 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.

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This paper presents a stator winding faults detection in induction generator based wind turbines by using artificial neural network (ANN). Stator winding faults of induction generators are the most common fault found in wind turbines. This fault may lead to wind turbine failure. Therefore, fault detection in induction generator based wind turbines is vital to increase the reliability of wind turbines. In this project, the mathematical model of induction generator based wind turbine was developed in MATLAB Simulink. The value of impedance in the induction generators was changed to simulate the inter-turn short circuit and open circuit faults. The simulated responses of the induction generators were used as inputs in the ANN model for fault detection procedures. A set of data was taken under different conditions, i.e. normal condition, inter-turn short circuit and open circuit faults as inputs for the ANN model. The target outputs of the ANN model were set as ‘0’ or ‘1’, based on the fault conditions. Results obtained showed that the ANN model can detect different types of faults based on the output values of the ANN model. In conclusion, the stator winding faults detection procedure for induction generator based wind turbines by using ANN was successfully developed.
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Abdullateef, 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.

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Induction motors are the backbone of the industries because they are easy to operate, rugged, economical and reliable. However, they are subjected to stator’s faults which damage the windings and consequently lead to machine failure and loss of revenue. Early detection and classification of these faults are important for the effective operation of induction motors. Stators faults detection and classification based on wavelet Transform was carried out in this study. The feature extraction of the acquired data was achieved using lifting decomposition and reconstruction scheme while Euclidean distance of the Wavelet energy was used to classify the faults. The Wavelet energies increased for all three conditions monitored, normal condition, inter-turn fault and phase-to-phase fault, as the frequency band of the signal decreases from D1 to A3. The deviations in the Euclidean Distance of the current of the Wavelet energy obtained for the phase-to-phase faults are 99.1909, 99.8239 and 87.9750 for phases A and B, A and C, B and C respectively. While that of the inter-turn faults in phases A, B and C are 77.5572, 61.6389 and 62.5581 respectively. Based on the Euclidean distances of the faults, Df and normal current signals, three classification points were set: K1 = 0.60 x 102, K2 = 0.80 x 102 and K3 = 1.00 x 102. For K2 ≥ Df ≥ K1 inter-turn faults is identified and for K3 ≥ Df ≥ K2 phase to phase fault identified. This will improve the induction motors stator’s fault diagnosis. Keywords: induction motor, stator fault classification, data acquisition system, Discrete Wavelet Transform
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Bouakoura, 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.

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Background: According to statistics, short circuit faults are the second most frequent faults in induction motors. Thus, in this paper, we investigated inter turn short circuit faults in their early stage. Methods: A new equivalent model of the induction motor with turn to turn fault on one phase has been developed. This model has been used to establish two schemes to estimate the severity of the short circuit fault. In the first scheme, the faulty model is considered as an observer, where a correction of an error between the measured and the estimated currents is the kernel of the fault severity estimator. However, to develop the second method, the model was required only in the training process of an artificial neural network (ANN). Since stator faults have a signature on symmetrical components of phase currents, the magnitudes and angles of these components were used with the mean speed value as inputs of the ANN. A simulation on MATLAB of both techniques has been performed with various stator frequencies. Results: The suggested schemes prove a unique efficiency in the estimation of incipient turn to turn fault. Besides, the ANN based scheme is less complex which reduces its implementation cost. Conclusion: To monitor the stator of an induction motor, the choice of the appropriate algorithm should be done according to the system in which the motor will be installed. If the motor is directing connected to the grid or fed via an inverter with a variable DC bus voltage, the observer would be better, otherwise, the ANN algorithm is recommended.
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Dissertations / Theses on the topic "Stator short circuit faults"

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Arkan, Muslum. "Stator fault diagnosis in induction motors." Thesis, University of Sussex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310244.

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Babu, 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.

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Stator inter-turn short circuit (ITSC) faults are one of the common sources for induction machine failure affecting their reliable operation. In this thesis, a finite element (FE) model is developed to study the ITSC fault. The FE model is developed for a prototype induction machine that has the potential to emulate an ITSC fault in the stator. With the developed FE model of the prototype machine, a simulation study is performed to understand the behaviour of various electrical and magnetic quantities in time- and frequency-domain. The investigated quantities are potentially good signatures of the stator winding faults and they are therefore suitable to use in a condition monitoring system. The prototype machine with ITSC faults has been tested in an experimental setup and the results are compared to the simulation and also to analytical results. For the fault current it was found a good agreement between analytical results, FE simulations and experimental results. Moreover, the FE simulation results of the negative-sequence stator current amplitude present a minor mismatch with the analytical and experimental results. The reason for this mismatch is due to an inaccurate knowledge of the prototype machine geometrical parameters.
Kortslutning 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.
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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.

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An estimated 30% of the faults in Induction Machine (IM) are related to its stator. These faults are mostly in the form of an Inter-Turn Short Circuit (ITSC) fault i.e., when two winding inside the stator of IM are shorted due to insulation failure. However, ITSC fault can be avoided by detecting them in advance and then scheduling the maintenance of the IM. This thesis studies two methods for detecting this incipient ITSC fault in a three-phase IM and then estimating the stator resistance unbalance due to the ITSC fault. The first method is based on the asymmetry caused in the IM by the ITSC fault. As a result of this asymmetry, the negative sequence components of the stator voltages and the stator currents are generated inside the IM. A healthy IM also have these negative sequence components due to the manufacturing process and the supply voltage unbalances. The characteristics and the compensation methods of these negative sequence components in a healthy IM are discussed. The results show that after compensating the negative sequence components in a healthy machine, they can be used for detecting an ITSC fault and then to calculate the fault quantities as well as the stator resistance unbalances. The second method for detecting an ITSC fault is based on analysing the stator resistance unbalances. A three-phase drive is used to inject DC voltage in the stationary reference frame. The DC current generated by this DC voltage is measured and then by applying Ohm’s law stator phase resistances are calculated. In a healthy IM, the phase resistances are balanced. However, in case of ITSC fault in any of the phases, the phase resistance of that phase deviates from those of the other two phases which can be utilized for detecting ITSC fault.
Uppskattningsvis 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.
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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.

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Devant la forte demande mondiale en énergie électrique, les alternateurs à diodes tournantes constituent une solution largement répandue dans les installations de génération d’électricité de fortes puissances (hydraulique, fossile et éolien) ainsi que dans les applications îlotées sous forme de groupes électrogènes ou de petits alternateurs intégrés dans les systèmes embarqués. La renommée de ce type d’alternateur s’est construite sur leurs robustes constitutions mécanique et électrique et sur leur parfaite adaptabilité au type de charge alimentée. Néanmoins, l’utilisation de ces machines dans des conditions de fonctionnement très contraignantes, que cela soit à cause des fortes puissances demandées par les applications industrielles ou des contraintes environnementales dans lesquelles travaillent les alternateurs isolés, engendre une recrudescence de défauts, principalement de types électriques, à l’intérieur du système. L’apparition de ces défaillances est extrêmement délétère pour des applications à haut niveau de service et dont un arrêt intempestif peut engendrer des coûts de maintenance et d’immobilisation très élevés pour les opérateurs. Devant la nécessité de planifier de façon optimisée les opérations de maintenance à effectuer sur les alternateurs, il est possible de mettre en place des stratégies de diagnostic qui surveillent l’apparition des principales défaillances susceptibles de toucher ce type de machine. Bien que les modifications imprévisibles du point de fonctionnement liées à la charge compliquent la tâche, il est envisageable de mettre en lumière la présence de défauts de court-circuit dans les bobinages ainsi que des défaillances de diodes dans le pont redresseur triphasé en étudiant les modifications des formes d’ondes des signaux électriques générés. Ce travail est décrit dans la présente thèse. Face au manque d’antécédents sur le sujet, une grande partie des recherches s’est focalisée sur la conception et la mise en place d’un modèle numérique d’alternateur à diodes tournantes représentatif des formes d’ondes réelles en régimes sain et défaillant, tache non triviale étant donné le caractère saillant des pôles de l’alternateur. Pour répondre à ces attentes, un processus original de co-simulation a été mis en place présentant une identification des inductances de l’alternateur sous Flux2D et une estimation numérique des équations différentielles du système sous Matlab. Cette modélisation fiable a par la suite permis une sélection d’indicateurs de diagnostic par analyse fréquentielle des signaux électriques qui sont capables, sans ajout de capteurs supplémentaires, d’informer l’utilisateur sur la présence de défauts à l’intérieur du système. Afin de s’assurer une bonne compréhension des phénomènes, un grand soin a été apporté à la justification théorique des modifications spectrales introduites par les défauts dans les signaux électriques. Une importante campagne d’essais expérimentaux a permis la validation des modèles sain et défaillant grâce à la réalisation, par la société Nidec Leroy- Somer, d’un alternateur capable de simuler des défauts de court-circuit inter-spires stator. Ces essais ont mis au jour la possibilité de détecter les défauts dans de nombreuses configurations de court-circuit, mais également la difficulté de les prévoir de façon anticipée, ouvrant par là même de nombreuses perspectives de recherche.
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Isaac, 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.

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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
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.
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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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.

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Orientador: Jozué Vieira Filho
Banca: 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
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8

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.

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Orientador: Carlos Roberto Minussi
Resumo: 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.
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9

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.

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Coordenação 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
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10

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.

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Permanent magnet synchronous machine drives are used more often. Although, synchronous machines drive also suffer from possible faults. This thesis is focused on the detection of the three-phase synchronous motor winding faults and the detection of the drive control loop sensors' faults. Firstly, a model of the faulty winding of the motor is presented. Effects of the inter-turn short fault were analyzed. The model was experimentally verified by fault emulation on the test bench with an industrial synchronous motor. Inter-turn short fault detection algorithms are summarized. Three existing conventional winding fault methods based on signal processing of the stator voltage and stator current residuals were verified. Three new winding fault detection methods were developed by the author. These methods use a modified motor model and the extended Kalman filter state estimator. Practical implementation of the algorithms on a microcontroller is described and experimental results show the performance of the presented algorithms in different scenarios on test bench measurements. Highly related motor control loop sensors fault detection algorithms are also described. These algorithms are complementary to winding fault algorithms. The decision mechanism integrates outputs of sensor and winding fault detection algorithms and provides an overall drive fault diagnosis concept.
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Books on the topic "Stator short circuit faults"

1

Brown, John C. An investigation into short circuit faults on the power supply of D.C.traction systems. Birmingham: University of Birmingham, 1988.

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Evans, 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.

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Diagnostics of Electrical Equipment Faults and Power Overhead Transmission Line Condition by Monitoring Systems: Short-Circuit Testing of Power Transformers. Nova Science Publishers, Incorporated, 2016.

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George 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.

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George 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.

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George 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.

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IEEE 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.

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Book chapters on the topic "Stator short circuit faults"

1

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.

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Xiangli, 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.

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Young-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.

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Li, 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.

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Li, 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.

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Thomson, 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.

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Sziray, 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.

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Hu, 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.

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Rajamany, 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.

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Pires, 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.

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Conference papers on the topic "Stator short circuit faults"

1

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.

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Wan, 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.

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Rotor vibration characteristics are first analyzed, when the rotor winding inter-turn short circuit fault, the air-gap dynamic eccentricity fault, the air-gap static eccentricity fault and the imbalance fault occurs. Next, the generator stator current characteristics on the faults also were analyzed, the results show that the faults can’t be diagnosed based only on rotor vibration characteristics or stator current characteristics. But considering the differences of compositive characteristics of the rotor vibration and stator current caused by different rotor faults, a new method of generator vibration fault diagnosis, based on compositive characteristics, is developed. Finally, the rotor vibration and stator current of a type SDF-9 generator is measured in the laboratory to verify the theoretical analysis presented above.
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Ebrahimi, 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.

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Lebaroud., 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.

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Niu, 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.

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He, 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.

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Khov, 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.

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Chen, 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.

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Sayed-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.

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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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Reports on the topic "Stator short circuit faults"

1

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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