Academic literature on the topic 'Stator winding turn fault'

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.<br>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.

Condition monitoring techniques can be employed to enhance reliability of electric machinery. The stator winding fault is one of the dominant causes for the failure of induction machines. In this work, the condition monitoring of an inverter-fed induction machine using high-frequency signal injection based technique is investigated. Initially, an analytical model of the induction machine with a stator inter-turn fault is developed. Subsequently, the behaviour of the induction machine in the presence of stator inter-turn fault is analyzed using the symmetrical component theory. Because of their use for fault diagnosis purposes, the analytical expressions for the fundamental and high-frequency symmetrical component currents are derived. The high-frequency signal injection is performed by adding a balanced three-phase high-frequency low-magnitude voltage to the fundamental excitation voltage. The resulting high-frequency negative-sequence current component can be used as reliable fault indicator to detect stator inter-turn faults. The effectiveness of the high-frequency negative-sequence current as a fault indicator is compared with the fundamental negative-sequence current, which is one of the traditionally used fault indicators for detecting these faults. The high-frequency signal injection technique proposed in this work is tested experimentally on a prototype machine in a laboratory set-up. The use of the proposed fault indicator is found to be advantageous when compared to the use of the traditional fault indicator for variable-frequency drives. In particular, it is shown that the proposed fault indicator is less dependent from the drive operating conditions than the traditional fault indicator.<br>Tillståndsövervakning är en teknik som kan användas för att förbättra tillförlitligheten hos elektriska maskiner. För asynkronmaskiner är fel i statorlindningen en av de dominerande orsakerna som leder till problem. I detta arbete undersöks tillståndsövervakning av en omriktarmatad asynkronmotor med hjälp av en högfrekvent signalinjektionsbaserad teknik. Inledningsvis utvecklas en analytisk modell av en asynkronmaskin med korsslutningsfel mellan varven i statorn. Därefter analyseras beteendet hos maskinen med hjälp av teorin för symmetriska komponenter. Analytiska uttryck för både grund- och övertoner härleds för de symmetriska komponenterna. Den högfrekventa signalinjektionen utförs genom att addera en liten högfrekvent trefasspänning till den matningsspänningen. Den resulterande högfrekventa negativa strömkomponenten kan användas som en tillförlitlig indikator för att upptäcka eventuella kortslutningar i statorlindningen. Förmågan som felindikator hos den högfrekventa negativa sekvensströmmen jämförs med den grundläggande negativa strömkomponentens förmåga, vilken är den traditionella indikatorn för att detektera dessa fel. Den högfrekventa signalinjiceringsmetoden som föreslås i detta arbete undersöks experimentellt på en prototypmaskin. Den föreslagna felindikatorn har visat sig vara fördelaktig jämfört med användningen av den traditionella felindikatorn för frekvensomriktare. I synnerhet visas att den föreslagna felindikatorn är mindre beroende av frekvensomriktarens driftsförhållanden än den traditionella felindikatorn.

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.

A stator turn fault in a safety-critical drive application must be detected at its initial stage and imperatively requires an evasive action to prevent a serious accident caused by an abrupt interruption in the drive s operation. However, this is much challenging for the case of an interior permanent magnet synchronous motor (IPMSM) drives because of the presence of the permanent magnets that cannot be turned off at will. This work tackles the problem of increase the stator turn fault tolerance of IPMSM drives in safety-critical applications. This objective is achieved by an on-line turn fault detection method and a simple turn fault-tolerant operating strategy. In this work, it is shown that a stator turn fault in a current-controlled voltage source inverter-driven machine leads to a reduced fundamental positive sequence component of the voltage references as compared to the machine without a turn fault for a given torque reference and rotating speed. Based on this finding, a voltage reference-based turn fault detection method is proposed. In addition, it is also revealed that an adjustment to the level of the rotating magnetic flux in an appropriate manner can yield a significant reduction in the propagation speed of the fault and possibly prevention of the fault from spreading to the entire winding. This would be accomplished without any hardware modification. Based on this principle, a stator turn fault-tolerant operating strategy for IPMSM drives maintaining drive s availability is proposed. To evaluate these turn fault detection method and fault-tolerant operating strategy, an electrical model and a thermal model of an IPMSM with stator turn faults are derived. All the proposed models and methods are validated through simulations and experiments on a 10kW IPMSM drive.

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.<br>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.

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.

La sophistication et la multiplication des systèmes de production de l'énergie électrique de nos jours, caractérisent les évolutions technologiques ainsi que celles des sociétés humaines. L'énergie électrique provenant des systèmes de production est un facteur essentiel pour le développement et l’amélioration des conditions de vie et des activités industrielles. Dans les systèmes de production de l'énergie électrique, comme dans le domaine des entraînements électriques, pouvant fonctionner à vitesse variable, la machine asynchrone à double alimentation (MADA) occupe de plus en plus de place. Cette machine est particulièrement appréciée car elle offre des avantages par rapport aux autres types de machines électriques comme la fiabilité, la robustesse et un coût moins élevé. C'est ce type de machine qui est monté dans la plupart des éoliennes actuelles.Cependant, malgré les avantages de cette machine, elle n'est pas à l'abri de défaillances. Ces dernières, les plus courantes, sont répertoriées comme suit : a) le court-circuit sur les enroulements statoriques et rotoriques, b) les cassures des barres du rotor, c) les défauts des roulements, d) les défauts d'excentricité de l'entre fer. Dans le cadre de la maintenance, ces types de défauts doivent être détectés à l'état naissant et être localisés, car ils risquent d'engendrer des coûts de maintenance élevés, des arrêts de production et des dégradations importantes du système.Le diagnostic d'un tel système incite les laboratoires de recherches aussi bien industriels que académiques, à mettre au point des dispositifs de surveillance performants. Plusieurs méthodes ont été étudiées dans ce domaine, afin de pouvoir réagir au plus vite et éviter une aggravation nuisible des défauts. Le but, étant d'assurer le fonctionnement du système, la production de l'énergie électrique et la diminution des coûts de maintenance. Ces études sont toujours d'actualité dans les différents centres de recherches.Ce manuscrit de thèse présente de nouvelles méthodologies de diagnostic de défauts de court-circuit entre spires dans l'enroulement statorique d'une MADA. Ces approches peuvent être développées à base d'un modèle ou issues des évolutions des amplitudes des composantes en harmoniques du signal vibratoire ou encore provenant de l'analyse des grandeurs caractéristiques de la forme géométrique des courants suivant les taux de court-circuit. Les grandeurs physiques exploitées sont les vibrations (seulement pour le cas expérimental) et les courants (cas théorique et expérimental). L'exploitation des méthodes présentées recourent à des techniques classiques comme la Transformée de Fourier (T.F) et l'Approche Vectorielle de Park (AVP). La T.F est utilisée afin d'observer l'évolution spectrale des harmoniques et plus particulièrement de leur amplitude. Ensuite, l'AVP est utilisée pour exploiter les grandeurs caractéristiques de la forme géométrique des courants. La MADA est modélisée analytiquement par le modèle des circuits à couplages multiples. Les approches proposées dans ce travail ont été simulées sur Matlab, puis validées sur un dispositif réel exploitant une machine asynchrone à rotor bobiné de 0,3kW. La MADA étudiée peut présenter un taux de court-circuit entre spires de 2,5%, 5%, 10%, 20%, 30% à 40% sur une phase (phase A)<br>Nowadays, the sophistication and the multiplication of electrical power systems, characterize technological and human society evolutions. Electrical energy from production systems is an essential factor for the development and improvement of living conditions and industrial activities. In electric power systems, as in the field of electric drives, which can be operated at variable speed, the Doubly Fed Induction machine (DFIM) occupies more and more space. This machine is particularly appreciated because it offers advantages over other types of electric machines such as reliability, robustness, and lower cost. It is this type of machine that is used in most current wind turbines.However, despite the advantages of this machine, it is not immune to failures. The most common ones are listed as follows: a) short circuit on stator and rotor windings, b) rotor bar breaks, c) bearing faults, d) eccentricity faults of the iron gap. In the case of maintenance, these types of defects must be detected in their early stages and located, because they can lead to high maintenance costs, production downtime and significant degradation.The diagnosis of such system encourages researches in laboratories, both industrial and academic, to develop effective monitoring devices. Many methods have been studied in this field, in order to be able to react as soon as possible and to avoid a harmful aggravation of defects. The aim is to ensure operation of the system, production of electrical energy and reduction of maintenance costs. These studies are still ongoing in the various research centers.This manuscript presents new methodologies to diagnose short circuit faults between turns in stator winding of a DFIM. These developed approaches are based on a model or from amplitudes of harmonic components of vibratory signal or from characteristics of geometric shape of currents according to short-circuit rates. The analized signals are vibrations (only for experimental case) and currents (theoretical and experimental cases). The presented methods use classical techniques such as the Fourier Transform (FT) and the Park Vector Approach (PVA). The FT is used to observe the spectral evolution of the harmonics and more particularly of their amplitude. Then, PVA is used to exploit characteristics of geometrical shape of currents. The DFIM is analytically modeled by multi-coupled circuit model. In this work, the proposed approaches were simulated on Matlab environment and validated on a real device using a 0.3kW wound rotor asynchronous machine (DFIM). The studied DFIM can be configurated with a short circuit rate between turns of 2.5%, 5%, 10%, 20%, 30% to 40% on one phase (phase A)

Grâce à leurs avancées techniques en termes de poids, performances et fiabilité, les machines synchrones sont de plus en plus utilisées dans le domaine de transport et en particuliers dans l’aéronautique. Les stratégies de maintenances de ces systèmes électriques sont alors indispensables afin d'éviter des surcouts liés à des temps d'arrêt non planifiés. Ce document propose une analyse des conséquences d'un défaut inter-spires intermittent naissant dans l'enroulement statorique d'une Machine Synchrone à Aimants Permanents (MSAP). Ce type de défaut correspond à l'état peu avancé d'un futur court-circuit permanent. Jusqu'à présent, les études menées se sont limitées à la détection de courts-circuits inter-spires permanents. L'objectif de cette analyse est de définir une méthode de détection de ce type de défaut qui soit facile à mettre en œuvre. A partir d'une étude analytique du courant statorique d'une MSAP contrôlée en courant en présence de court-circuit intermittent, nous avons étudié l'impact des différentes grandeurs influençant la perturbation du courant. Nous avons constaté que la forme de la perturbation créée par le défaut était toujours la même et qu'elle était la signature du défaut intermittent dans le courant. Par la suite cette étude analytique a été validée expérimentalement. Dans la partie suivante nous avons étudié la sensibilité des méthodes de détection des courts-circuits inter-spires permanents appliquées au cas du court-circuit intermittent. Ces méthodes se sont révélées inadaptées pour la détection du défaut étudié dans ce travail. Nous avons donc proposé une méthode dédiée qui est basée sur la détection de la signature du défaut et qui utilise une transformation en ondelette adaptée. Il s'agit d'une méthode de détection de forme qui permet non seulement de détecter le défaut intermittent mais aussi de le distinguer des autres types de défauts. La performance de la méthode a été validée par les résultats de simulation et de manipulation. Dans une dernière partie, une étude plus générale sur le suivi de vieillissement des enroulements est proposée. Elle est basée sur le suivi de l'évolution des courbes d'admittance hautes fréquences d'un bobinage au cours du temps en utilisant les fonctions de transfert de ce dernier<br>Thanks to technical advances in terms of weight, performance and reliability, synchronous machines are increasingly used in the transport field and especially in aeronautics. The maintenance strategies of these electrical systems are essential to avoid extra costs associated with unscheduled downtime. This document offers a study on the intermittent inter-turn fault occurring in the stator winding of a Permanent Magnet Synchronous Machine (PMSM) and its consequences. This type of fault correspond to the emerging state for a future permanent short circuit condition. So far, studies have been limited to the detection of continuous inter-turn short circuits. The main purpose of this analysis is to define a detection method for this type of fault easy to implement. Based on the stator current analytical study of a PMSM current controlled in presence of intermittent short circuit, we had studied the impact of different variables influencing the current disturbance. We had found that the shape of the disturbance created by the fault was always the same and that it was the fault signature in the current signal. Later this analytical study was validated experimentally. In the next part we had studied the sensitivity of continuous short circuits detection methods applied in the case of intermittent short circuit. These methods have been proved unsuitable to detect the defect studied in this work. Therefore, we had proposed a dedicated method based on the fault signature identification using an adapted wavelet transform. It is a pattern detection method able to detect the intermittent fault and to distinguish it from other types of defects. The performance of the method was validated by simulation and experimental results. In the last part, a more general study concerning the winding health monitoring is proposed. It uses transfer functions and it is based on the monitoring over time of the winding high frequencies admittance curves evolution