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Artykuły w czasopismach na temat "Bruit des éoliennes"
Schellenberger, Thomas, i Raphaël Schneider. "Droit des pollutions et des nuisances". Revue Juridique de l'Environnement 43, nr 1 (2018): 167–79. http://dx.doi.org/10.3406/rjenv.2018.7221.
Pełny tekst źródła"Exposition de la population au bruit émis par les éoliennes en France métropolitaine". Environnement Risques & Santé 21, nr 5 (27.09.2022): 355–60. http://dx.doi.org/10.1684/ers.2022.1675.
Pełny tekst źródłaRozprawy doktorskie na temat "Bruit des éoliennes"
Kayser, Bill. "Estimation des incertitudes de modélisation du bruit des éoliennes". Thesis, Le Mans, 2020. http://www.theses.fr/2020LEMA1035.
Pełny tekst źródłaThere is a major societal challenge to study the emission and propagation of noise emitted by wind turbines, and in particular to quantify the uncertainty in the estimation of sound levels. Although these sound levels are relatively low compared to those generated by other acoustic sources in the environment (e.g. land transport), noise pollution from wind turbines is often highlighted as a potential nuisance. Thus, this thesis work aims to quantify the spatial and frequency dependence of the uncertainties encountered in environmental acoustics, and in particular concerning wind turbine noise. To do so, a coupling is made between an acoustic emission model allowing to take into account the acoustic specificities of wind turbines (spectrum and directivity), and an acoustic propagation model allowing to take into account the effects of the atmosphere (thermal and aerodynamic vertical profiles) and the ground effects (absorption and roughness) on acoustic propagation. A sensitivity analysis is then carried out to determine the environmental parameters that have the greatest influence on the dispersion of sound levels. Following the development of a metamodel, an uncertainty analysis is carried out to estimate the total variability of the sound levels. Finally the method is applied to some examples of situations characteristic of the wind turbine noise
Mascarenhas, David. "Physics-based synthesis of wind turbine noise". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAE020.
Pełny tekst źródłaIt is known that the wind turbine noise is a potential source of disturbance and annoyance for the people in the vicinity of the wind farms. The work presented in the thesis addressed the problem of wind turbine noise by developing a physic-based model to synthesize and study it. The synthesis model detailed here advances from the frequency-domain model for wind turbine noise developed by Tian and Cotté and revisits certain components in light of the recent literature. A synthesis tool is created to convert the frequency domain noise predictions to a time signal with the help of a window function. The designed window function is made to account for the difference in the propagation time observed due to the rotation of the blades.A few test cases of the synthesized sound can be found in the thesis for different scenarios. The model is finally compared to the field measurements done for an entire wind farm and show fairly good results for the source as well as the propagation part. The developed model is a useful tool which can be used for psychoacoutic evaluation to understand the perception and annoyance factor of wind turbine noise. Along with obtaining the spectral levels of the expected noise from the wind farm, the tool also produces audible signals that can be further used for the desired purpose. Thus making it a useful tool that abridges the gap between citizens, local authorities and acousticians
Salameh, Jack. "Approche par contrôle actif dans le cadre de l'optimisation de la durée de vie des éoliennes". Thesis, La Rochelle, 2019. http://www.theses.fr/2019LAROS026.
Pełny tekst źródłaThis thesis entitled "Active control for wind turbine lifetime expectancy optimization" studies the operation of wind turbines and aims to reduce disturbance through an active control strategy. Wind turbines are known to operate under harsh environmental conditions mainly related to random wind speeds. The wind profile induces two disturbance components known as the wind shear and tower shadow. These components produce a disturbed aerodynamic torque causing stress, fatigue, and mechanical component failure. Chapter 1 introduces the wind turbine theory and all related mechanical and electrical subsystem. The extended Kalman filter (EKF) is then introduced to show the necessity of signal processing and diagnosis for disturbance isolation and detection. Chapter 2 presents a new modified Sliding Window Empirical Mode Decomposition (SWEMD) method as a signal processing method capable of better isolating the disturbance component. It is concluded that after the SWEMD one can accurately diagnose the wind shear and tower shadow disturbance frequency signature. In chapter 3 an estimation method based on the Unknown Input Observer (UIO) is applied in order to estimate the disturbance in the wind turbine. The UIO shows great results in accurately estimating the disturbance. Chapter 4 introduces the active control Linear Parameter Varying (LPV)-based strategy for torque ripple attenuation. The isolated disturbance by the SWEMD, and the estimated disturbance through the UIO are used as the LPV control input in order to generate a current control command. The control command is then injected into the generator in order to reduce the disturbance effect on the drivetrain. For both isolation and estimation results show good aerodynamic disturbance attenuation, while the UIO showed better results than those of the SWEMD. Chapter 5 presents the experimental setup used to validate the theoretical work. A test bench at the University of Poitiers is used to imitate the operation of the wind turbine. All the results matched the ones found in the theoretical tests
Mortelette, Loïc. "Crissement des freins de giration de nacelles d'éoliennes : éléments de compréhension et influence du matériau de friction". Thesis, Lille 1, 2012. http://www.theses.fr/2012LIL10090/document.
Pełny tekst źródłaIn order to produce electricity, a wind turbine needs to be face to the wind. The system allowing its orientation is placed between the tower and the nacelle and is called ‘yaw’. Due to the contact between friction pads and disc during the rotation phases, squeal noise can occur, the braking forces being used to control the nacelle rotation. In the aim of reducing and even suppressing the noise, a scientific approach has been set up to understand the phenomena involved, including the structure and the friction material aspects, no such study has ever been carried on in the wind turbine domain. The first step has consisted in characterizing the problem in real conditions on wind turbines. The collected data and an extended bibliographic study have been used to define a strategy: globally, the study is based both on experimental investigations and numerical simulations. The influence of the friction material has been highlighted: several materials have been investigated, one of them being a “improvement” of a commercial material initially “noisy”. Those friction materials are also described and characterized regarding their mechanical properties and the rubbing surfaces have been observed after tests. In the end, that study has enable to control and identify some influent parameters as the role of the friction pads, bringing a better understanding of the phenomena involved in that squealing noise problematic in order to develop new improvement solutions to reduce noise
Dumortier, Baldwin. "Contrôle acoustique d'un parc éolien". Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0131/document.
Pełny tekst źródłaCurrently, acoustic studies are required to set wind farms up. They must ensure the tranquility of the inhabitants around the farms in accordance with current regulations. For this purpose, acoustic measurements are made during a couple of weeks. When measuring, the wind turbines are periodically stopped in order to evaluate the difference between ambient noise levels (with the turbines on) and residual noise levels (with the turbines off). A curtailment plan is then computed and sent to the wind farm owner in order to set it up in the local turbine control system (SCADA). Currently, the curtailment plan roughly depends on the weather conditions and the time of the day which are allegedly correlated to the acoustic variables. In practice, it frequently leads to violations of the acoustic constraints or electrical power loss. This is because the acoustic conditions constantly and strongly evolve over time: the wind turbine noise level finely depends on the weather conditions and the residual noise level depends on all the other acoustic sources and has therefore a stochastic nature. The goal of the thesis is to design a principled real-time control algorithm for wind farms. To do so, we investigate the use of a black-box source separation system that estimates the residual noise level and the wind turbine noise level. We first provide a theoretical formulation of the problem by accounting for specific practical issues, by defining the variables of the problem and by binding these issues to the state of the art. Then, we propose two complete control solutions and run an experimental evaluation. The first solution is a deterministic algorithm based on a constrained combinatorial optimization algorithm, which is inspired by the current approach for controlling wind farms while exploiting the source separation system. Moreover, we present a study of its ability to fulfill the French acoustic constraints that are computed as temporal medians of the acoustic variables. The second solution is stochastic and based on a state-space model defined by means of Gaussian uncertainties. It features a nonlinear Kalman filter in order to fuse the uncertainties of the model and of the source separation system, an Expectation-Maximization algorithm that computes the uncertainties for a specific farm, and a robust variant of the deterministic algorithm that takes the estimated uncertainties into account when computing the optimal command
Tian, Yuan. "Modélisation des sources de bruit d'une éolienne et propagation à grande distance". Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLY003/document.
Pełny tekst źródłaThe purpose of this work is to model wind turbine noise sources and propagation in the atmosphere in order to better understand the characteristics of wind turbine noise at long range and to help wind turbine manufacturers and wind farm developers meet the noise regulations. By coupling physically-based aeroacoustic source and propagation models, we are able to predict wind turbine noise spectra, directivity and amplitude modulation in various atmospheric conditions.Broadband noise generated aerodynamically, namely turbulent inflow noise, trailing edge noise and separation/stall noise, is generally dominant for a modern wind turbine. Amiet's analytical model is chosen to predict turbulent inflow noise and trailing edge noise, considering several improvements to the original theory: 1, an empirical leading edge thickness correction is introduced in the turbulent inflow noise calculation; 2, a wall pressure fluctuation spectrum model proposed recently for adverse pressure gradient flow is used in the trailing edge noise predictions. The two models are validated against several wind tunnel experiments from the literature using fixed airfoils.Amiet's model is then applied on a full-size wind turbine to predict the noise emission level in the near field. Doppler effect and blade rotation are taken into account. Cases with constant wind profiles and no turbulence are used first, then wind shear and atmospheric turbulence effects obtained from Monin-Obukhov similarity theory are included. Good agreements against field measurements are found when both turbulent inflow noise and trailing edge noise are considered. Classical features of wind turbine noise, such as directivity and amplitude modulation, are recovered by the calculations. Comparisons with a semi-empirical model show that separation noise might be significant in some circumstances.Next, Amiet's theory is coupled with propagation models to estimate noise immission level in the far-field. An analytical model for the propagation over an impedance ground in homogeneous conditions is studied first. The ground effect is shown to modify the shape of the noise spectra, and to enhance the amplitude modulation in some third octave bands. A method to couple the source model to a parabolic equation code is also proposed and validated to take into account atmospheric refraction effects. Depending on the propagation direction, noise levels vary because the ground effect is influenced by wind shear and a shadow zone is present upwind. Finally, the point source assumption is reviewed considering both the analytical and numerical propagation models
Tian, Yuan. "Modélisation des sources de bruit d'une éolienne et propagation à grande distance". Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLY003.
Pełny tekst źródłaThe purpose of this work is to model wind turbine noise sources and propagation in the atmosphere in order to better understand the characteristics of wind turbine noise at long range and to help wind turbine manufacturers and wind farm developers meet the noise regulations. By coupling physically-based aeroacoustic source and propagation models, we are able to predict wind turbine noise spectra, directivity and amplitude modulation in various atmospheric conditions.Broadband noise generated aerodynamically, namely turbulent inflow noise, trailing edge noise and separation/stall noise, is generally dominant for a modern wind turbine. Amiet's analytical model is chosen to predict turbulent inflow noise and trailing edge noise, considering several improvements to the original theory: 1, an empirical leading edge thickness correction is introduced in the turbulent inflow noise calculation; 2, a wall pressure fluctuation spectrum model proposed recently for adverse pressure gradient flow is used in the trailing edge noise predictions. The two models are validated against several wind tunnel experiments from the literature using fixed airfoils.Amiet's model is then applied on a full-size wind turbine to predict the noise emission level in the near field. Doppler effect and blade rotation are taken into account. Cases with constant wind profiles and no turbulence are used first, then wind shear and atmospheric turbulence effects obtained from Monin-Obukhov similarity theory are included. Good agreements against field measurements are found when both turbulent inflow noise and trailing edge noise are considered. Classical features of wind turbine noise, such as directivity and amplitude modulation, are recovered by the calculations. Comparisons with a semi-empirical model show that separation noise might be significant in some circumstances.Next, Amiet's theory is coupled with propagation models to estimate noise immission level in the far-field. An analytical model for the propagation over an impedance ground in homogeneous conditions is studied first. The ground effect is shown to modify the shape of the noise spectra, and to enhance the amplitude modulation in some third octave bands. A method to couple the source model to a parabolic equation code is also proposed and validated to take into account atmospheric refraction effects. Depending on the propagation direction, noise levels vary because the ground effect is influenced by wind shear and a shadow zone is present upwind. Finally, the point source assumption is reviewed considering both the analytical and numerical propagation models
Bai, Hao. "Machine learning assisted probabilistic prediction of long-term fatigue damage and vibration reduction of wind turbine tower using active damping system". Thesis, Normandie, 2021. http://www.theses.fr/2021NORMIR01.
Pełny tekst źródłaThis dissertation is devoted to the development of an active damping system for vibration reduction of wind turbine tower under gusty wind and turbulent wind. The presence of vibrations often leads to either an ultimate deflection on the top of wind tower or a failure due to the material’s fatigue near the bottom of wind tower. Furthermore, given the random nature of wind conditions, it is indispensable to look at this problem from a probabilistic point of view. In this work, a probabilistic framework of fatigue analysis is developed and improved by using a residual neural network. A damping system employing an active damper, Twin Rotor Damper, is designed for NREL 5MW reference wind turbine. The design is optimized by an evolutionary algorithm with automatic parameter tuning method based on exploitation and exploration
Gliga, Lavinius ioan. "Diagnostic d'une Turbine Eolienne à Distance à l'aide du Réseau de Capteurs sans Fil". Thesis, Normandie, 2019. http://www.theses.fr/2019NORMR063/document.
Pełny tekst źródłaDirect Drive Wind Turbines (DDWTs) are equipped with Permanent Magnet Syn- chronous Generators (PMSGs). Their three most common failures are demagnetization, ec- centricity (static, dynamic and mixed) and inter-turn short circuit. Machine Current Signa- ture Analysis is often used to look for generator problems, as these impairments introduce additional harmonics into the generated currents. The Fast Fourier Transform (FFT) is utilized to compute the spectrum of the currents. However, the FFT calculates the whole spectrum, while the number of possible faults and the number of introduced harmonics is low. The Goertzel algorithm, implemented as a filter (the Goertzel filter), is presented as a more efficient alternative to the FFT. The spectrum of the currents changes with the wind speed, and thus the detection is made more difficult. The Extended Kalman Filter (EKF) is proposed as a solution. The spectrum of the residuals, computed between the estimated and the generated current, is constant, regardless of the wind speed. However, the effect of the faults is visible in the spectrum. When using the EKF, one challenge is to find out the covariance matrix of the process noise. A new method was developed in this regard, which does not use any of the matrices of the filter. DDWTs are either placed in remote areas or in cities. For the monitoring of a DDWT, tens or hundreds of kilometers of cables are necessary. Wireless Sensor Networks (WSNs) are suited to be used in the communication infrastructure of DDWTs. WSNs have lower initial and maintenance costs, and they are quickly installed. Moreover, they can complement wired networks. Different wireless technologies are com- pared - both wide area ones, as well as short range technologies which support high data rates