83 research outputs found
Induction machine fault detection enhancement using a stator current high resolution spectrum
No full textFault detection in squirrel cage induction machines based on stator current spectrum has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. In this paper, a modified version of MUSIC algorithm has been developed based on the faults characteristic frequencies. This method has been used to estimate the stator current spectrum. Then, an amplitude estimator has been proposed and a fault indicator has been derived for fault severity measurement. Simulated stator current data issued from a coupled electromagnetic circuits approach has been used to prove the appropriateness of the method for air gap eccentricity and broken rotor bars faults detection
Interception des signaux issus de communications MIMO
No full textMultiple-Input Multiple-Output (MIMO) communications improve the data rates and the robustness of a wireless link by using the spatial diversity of the propagation channel. Because of its high performances, MIMO systems are the catalyst for the next revolution in wireless systems and would play a key role for the development of future networks and cell phones standards. In this PhD thesis, we investigate the problem of the blind recognition of the MIMO parameters under a non-cooperative environment i.e. when the transmitter parameters, the propagation channel and the noise level are unknown at the receiver side. This context occurs in various civilian and military situations. Assuming that the synchronization has been previously performed, we propose new algorithms devoted to the blind recognition of the number of transmitter antennas, of the space-time coding and of the modulation.Les communications multi-antennes, désignées par l'acronyme MIMO (Multiple-Input Multiple-Output), permettent d'atteindre des débits et une qualité de transmission élevés en exploitant la diversité spatiale du canal de propagation. De part leurs performances, les systèmes MIMO sont au coeur des futurs standards de réseaux sans-fil et de téléphonie mobile et devraient occuper prochainement une place importante dans le canal hertzien. Cette thèse, intitulée "Interception des signaux issus de communications MIMO", aborde ces systèmes dans le contexte non coopératif c'est-à-dire lorsque le récepteur ne dispose d'aucune information sur la configuration de l'émetteur, le canal de propagation et sur le niveau de bruit. L'étude se situe en aval des étapes de synchronisation et suppose que les échantillons reçus sont préalablement ramenés en bande de base et échantillonnés au rythme d'un échantillon par symbole. Sous ces hypothèses, nous proposons plusieurs algorithmes pour identifier en aveugle les paramètres de l'émetteur tels que le nombre d'antennes, le codage spatio-temporel et la modulation. Les applications concernées sont variées et touchent aussi bien le domaine civil (développement de récepteurs MIMO auto-configurants) que le domaine militaire (guerre électronique)
A Spatialised Sound environment Synthesizer
No full textInternational audienceThe synthesis of spatialised sound environment is a mean to increase the "sense of presence" of a listener in a virtual environment. We define sound environment synthesis as the audio synthesis of sounds other than speech or music and which contribute to the ambience of the sound scene. This paper first proposes a classification of sounds, and a state of the art in sound synthesis and spatialisation. Then the architecture of an interactive spatialised sound environment synthesizer is described. This work is part of a more general research framework which aim is to evaluate the contribution of 3D sound in terms of realism, immersion, pleasure, etc, in different applications such as virtual reality, telecommunications, simulators, music..
Voltage Sags Estimation in Three-Phase Systems using Unconditional Maximum Likelihood Estimation
No full textTypo Correction on equation (19).International audienceThis paper focuses on the estimation of voltage sags in three-phase power systems. Specifically, it proposes a new approach for estimating the amplitude and phase angle of the sag based on the Unconditional Maximum Likelihood technique. As opposed to other techniques, this approach is well suited for signals with amplitude and/or phase modulation such as those encountered in smart grid applications. Simulation and experimental results illustrate the effectiveness of the proposed approach
Phasor estimation using conditional maximum likelihood: Strengths and limitations
No full textInternational audienceThis paper focuses on the estimation of the phasor parameters in three-phase power systems for smart grid monitoring. Specifically, it investigates the use of the Conditional Maximum Likelihood (ML) for phasor parameter estimation. The contribution of this paper is twofold. First, it presents the condition on the signal model for identifiability of the phasor parameters. Then, it shows that the Conditional Maximum Likelihood estimator has a simple closed form expression, which can be determined from simple geometrical properties. Simulation results illustrate the effectiveness of the proposed approach for the estimation of the phasor amplitude and angle shift under dynamic conditions
Bearing Fault Detection in DFIG-Based Wind Turbines Using the First Intrinsic Mode Function
No full textWind energy conversion systems have become a focal point in the research of renewable energy sources. In order to make the DFIG-based wind turbines so competitive as the classical electric power stations it is important to reduce the operational and maintenance costs by continuously monitoring the condition of these systems. This paper provides a method for bearing fault detection in DFIG-based wind turbines. The proposed method uses the first Intrinsic Mode Function (IMF) of the stator current signal. After extracting the first IMF, amplitude-demodulation is performed to reveal a generator bearing fault. Experimental results show that the proposed method significantly improves the result of classical amplitude-demodulation techniques for failure detection
An Improved Algorithm for Power System Fault Type Classification based on Least Square Phasor Estimation
No full textInternational audienc
Classification of three-phase power disturbances based on model order selection in smart grid applications
No full textInternational audienceThis paper deals with a new classification techniques for power quality analysis. Specifically, the proposed technique aims at discriminating between four classes, where each class depends on the number of non-zero symmetrical components. By reformulating the classification problem as a pure model order selection one, we propose a classifier based on Information Theoretical Criteria. It yields the highest statistical performances. The performances of this proposed classifier are evaluated using Monte Carlo simulations with synthetic three-phase signals. Simulation results illustrate the effectiveness of the proposed classifier for power quality disturbances classification
EEMD-based windturbinebearingfailuredetectionusing the generatorstatorcurrenthomopolarcomponent
No full textInternational audienceFailure detection has always been a demanding task in the electrical machines community; it has become more challenging in wind energy conversion systems because sustainability and viability of wind farms are highly dependent on the reduction of the operational and maintenance costs. Indeed the most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the generator health degeneration, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper provides then an assessment of a failure detection techniques based on the homopolar component of the generator stator current and attempts to highlight the use of the ensemble empirical mode decomposition as a tool for failure detection in wind turbine generators for stationary and non stationary cases
A Comparative Study of Time-Frequency Representations for Fault Detection in Wind Turbine
No full textTo reduce the cost of wind energy, minimization and prediction of maintenance operations in wind turbine is of key importance. In variable speed turbine generator, advanced signal processing tools are required to detect and diagnose the generator faults from the stator current. To detect a fault in non-stationary conditions, previous studies have investigated the use of time-frequency techniques such as the Spectrogram, the Wavelet transform, the Wigner-Ville representation and the Hilbert-Huang transform. In this paper, these techniques are presented and compared for broken-rotor bar detection in squirrel-cage generators. The comparison is based on several criteria such as the computational complexity, the readability of the representation and the easiness of interpretatio
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