Electrical, Control and Communication Engineering, 2014
In electromagnetic problems, the problem geometry may not always be exactly known. One example of... more In electromagnetic problems, the problem geometry may not always be exactly known. One example of such a case is a rotating machine with random-wound windings. While spectral stochastic finite element methods have been used to solve statistical electromagnetic problems such as this, their use has been mainly limited to problems with uncertainties in material parameters only. This paper presents a simple method to solve both static and time-harmonic magnetic field problems with source currents in random positions. By using an indicator function, the geometric uncertainties are effectively reduced to material uncertainties, and the problem can be solved using the established spectral stochastic procedures. The proposed method is used to solve a demonstrative single-conductor problem, and the results are compared to the Monte Carlo method. Based on these simulations, the method appears to yield accurate mean values and variances both for the vector potential and current, converging clo...
Le Centre pour la Communication Scientifique Directe - HAL - Université de Nantes, Jul 15, 2019
In the field of computational electromagnetics, taking into account the motion of the rotor in el... more In the field of computational electromagnetics, taking into account the motion of the rotor in electrical machines requires special attention. In this work, we propose to compare the solutions obtained by the Harmonic Balance Finite Element Method (HB-FEM) coupled, on the one hand, with the A formulation and, on the other hand, with Ω formulation with those obtained by the reference method namely, the Time Stepping Finite Element Method (TS-FEM). This comparison is carried out in the case of electrical machines while considering the movement of the rotor. To this issue, a permanent magnet machine is considered.
2016 IEEE Conference on Electromagnetic Field Computation (CEFC), 2016
HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific re... more HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 2013
In this paper, we analyze the influence of the uncertainties on the behavior constitutive laws of... more In this paper, we analyze the influence of the uncertainties on the behavior constitutive laws of ferromagnetic materials on the behavior of a turboalternator. A simple stochastic model of anhysteretic non-linear B(H) curve is proposed for the ferromagnetic yokes of the stator and the rotor. The B(H) curve is defined by five random parameters. We quantify the influence of the variability of these five parameters on the flux linkage of one phase of the stator winding depending on the excitation current I. The influence of each parameter is analyzed via the Sobol indices. With this analysis, we can determine the most influential parameters for each state of magnetization (according to the level of I) and investigate where the characterization process of the B(H) curve should focus to improve the accuracy of the computed flux linkage.
International Journal of Computer Mathematics, 2014
In this paper, we present a framework to deal with uncertainty quantification in case where the r... more In this paper, we present a framework to deal with uncertainty quantification in case where the ranges of variability of the random parameters are ill-known. Namely the physical properties of the corrosion product (magnetite) which frequently clogs the tube support plate of steam generator, which is inaccessible in nuclear power plants. The methodology is based on Polynomial Chaos (PC) for the direct approach and on Bayesian inference for the inverse approach. The direct Non-Intrusive Spectral Projection (NISP) method is first employed by considering prior probability densities and therefore constructing a PC surrogate model of the large-scale NDT finite element model. To face the prohibitive computational cost underlying the high dimensional random space, an adaptive sparse grid technique is applied on NISP resulting in drastic time reduction. The PC surrogate model, with reduced dimensionality, is used as a forward model in the Bayesian procedure. The posterior probability densities are then identified by inferring from few noisy experimental data. We demonstrate effectiveness of the approach by identifying the most influential parameter in the clogging detection as well as a variability range reduction.
COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, 2020
Purpose This paper aims to go deeper on the analysis of the shaft voltage of large turbogenerator... more Purpose This paper aims to go deeper on the analysis of the shaft voltage of large turbogenerators. The main interest of this study is the investigation process developed. Design/methodology/approach The analysis of the shaft voltage because of several defects is based on a two-dimensional (2D) finite element modeling. This 2D finite element model is used to determine the shaft voltage because of eccentricities or rotor short-circuit. Findings Dynamic eccentricities and rotor short circuit do not have an inherent impact on the shaft voltage. Circulating currents in the stator winding because of defects impact the shaft voltage. Originality/value The original value of this paper is the investigation process developed. This study proposes to quantify the impact of a smooth stator and then to explore the contribution of the real stator winding on the shaft voltage.
The Non-Intrusive Spectral Projection (NISP) method is widely used for uncertainty quantification... more The Non-Intrusive Spectral Projection (NISP) method is widely used for uncertainty quantification in stochastic models. The determination of the expansion of the solution on the polynomial chaos requires the computation of multidimensional integrals. An automatic adaptive algorithm based on nested sparse grids has been developed to evaluate those integrals. The adapted algorithm takes into account the weight of each random variable with respect to the output of the model. To achieve that it constructs anisotropic sparse grid of the mean, leading to a reduction of the number of numerical simulations. Furthermore, the spectral form of the solution is explicitly identified from the constructed quadrature scheme. Numerical results obtained on an industrial application in NDT demonstrate the efficiency of the proposed method.
In this paper, we present a framework to deal with uncertainty quantification in case where the r... more In this paper, we present a framework to deal with uncertainty quantification in case where the ranges of variability of the random parameters are ill-known. Namely the physical properties of the corrosion product (magnetite) which frequently clogs the tube support plate of steam generator, which is inaccessible in nuclear power plants. The methodology is based on Polynomial Chaos (PC) direct approaches and on Bayesian inference for inverse problems. The direct Non Intrusive Spectral Projection (NISP) method is first employed by considering prior probability densities and therefore construct a PC surrogate model of the large-scale NDT finite element model. To face the prohibitive computational cost underlying the high dimensional random space, the adaptive sparse grid technique is applied on NISP resulting in a significant time reduction. The PC surrogate model, with reduced dimensionality, is used as a forward model in the Bayesian procedure. The posterior probability densities are then identified by inferring from few noisy experimental data. We demonstrate the effectiveness of the approach on the identification the permeability and conductivity of the magnetite using Sax ratio measurements.
This study presents a strategy for estimating the states and the load torque to implement a feedb... more This study presents a strategy for estimating the states and the load torque to implement a feedback linearisation controller for induction motor drives. The multivariable control is carried out using input-output linearisation feedback law in order to track profiles of the rotational speed and the rotor flux amplitude. The unknown load torque is compensated by an estimator based on the speed error. The state estimation requires only the measurements of the stator voltagescurrents. The estimation method is not invasive as no mechanical sensors are needed. Experimental platform equipped with sensors at the load side, for measuring the speed and the torque of the motor driven by the Opal-RT real-time system, was implemented to verify the accuracy of the proposed estimation method to implement the multivariable control.
This paper presents bearings faults detection and isolation system for a wind energy conversion s... more This paper presents bearings faults detection and isolation system for a wind energy conversion system (WECS). For this, and contrary to the traditional methods often used and based on the frequency and/or the vibration analysis of generator signals, this novel approach is based on the temporal analysis of electrical signals (current or voltage) of the generator. The method is based on the observer scheme, composed of a time-varying Kalman filter and the strategy of the mean-residual to generate new residual capable to detect and quantify all bearings faults types. The proposed system has been validated on signals of a doubly-fed induction generator and the simulation results approve its efficiency.
This study presents a new strategy for estimating the states (rotor flux and speed) and the load ... more This study presents a new strategy for estimating the states (rotor flux and speed) and the load torque to implement a multivariable controller for a sensorless three-phase squirrel-cage induction machine in wind energy conversion systems. The multivariable control is carried out using input–output feedback law and its objective is to track profiles of the rotational speed and the rotor flux amplitude. The state estimation considerably improves the performance of rotor flux based model reference adaptive system in the variable speed region of operation. The technique uses Kalman filter as a rotor flux observer and an artificial neural network adaption mechanism to estimate the rotor speed. The state estimation requires only the measurements of the stator voltages and currents. The estimation method, for both states and torque, is not invasive as no mechanical sensors are needed. The wind energy conversion system and the proposed control-estimation techniques are simulated in Matlab/ Simulink software platform and tested using the OPAL-RT real-time simulator (OP5600) to verify the accuracy of the proposed control-estimation method.
he approximation of a complex function by an Artificial Neural Networks (ANN) of Radial basis Fun... more he approximation of a complex function by an Artificial Neural Networks (ANN) of Radial basis Function (NRF) conducts to large size architectures (a considerable number of neurons in the hidden layer) which minimize the quality of the network generation. This paper develops and implements an algorithm based on the Newton’s method for learning and searching for an optimal structure of a radial basis network. The algorithm reduces automatically the number of neurons in the hidden layer of the ANN and also reaches the minimal architecture without deteriorating the learning error. Tovalidate the algorithm, simulation of filtering noise from a noisy sinusoidal signal has been performed using MATLAB/SIMULINK. Satisfying results have been obtained and application as a filter for fault detection in a Wind Energy Conversion System (WECS) is intended.
Electrical, Control and Communication Engineering, 2014
In electromagnetic problems, the problem geometry may not always be exactly known. One example of... more In electromagnetic problems, the problem geometry may not always be exactly known. One example of such a case is a rotating machine with random-wound windings. While spectral stochastic finite element methods have been used to solve statistical electromagnetic problems such as this, their use has been mainly limited to problems with uncertainties in material parameters only. This paper presents a simple method to solve both static and time-harmonic magnetic field problems with source currents in random positions. By using an indicator function, the geometric uncertainties are effectively reduced to material uncertainties, and the problem can be solved using the established spectral stochastic procedures. The proposed method is used to solve a demonstrative single-conductor problem, and the results are compared to the Monte Carlo method. Based on these simulations, the method appears to yield accurate mean values and variances both for the vector potential and current, converging clo...
Le Centre pour la Communication Scientifique Directe - HAL - Université de Nantes, Jul 15, 2019
In the field of computational electromagnetics, taking into account the motion of the rotor in el... more In the field of computational electromagnetics, taking into account the motion of the rotor in electrical machines requires special attention. In this work, we propose to compare the solutions obtained by the Harmonic Balance Finite Element Method (HB-FEM) coupled, on the one hand, with the A formulation and, on the other hand, with Ω formulation with those obtained by the reference method namely, the Time Stepping Finite Element Method (TS-FEM). This comparison is carried out in the case of electrical machines while considering the movement of the rotor. To this issue, a permanent magnet machine is considered.
2016 IEEE Conference on Electromagnetic Field Computation (CEFC), 2016
HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific re... more HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 2013
In this paper, we analyze the influence of the uncertainties on the behavior constitutive laws of... more In this paper, we analyze the influence of the uncertainties on the behavior constitutive laws of ferromagnetic materials on the behavior of a turboalternator. A simple stochastic model of anhysteretic non-linear B(H) curve is proposed for the ferromagnetic yokes of the stator and the rotor. The B(H) curve is defined by five random parameters. We quantify the influence of the variability of these five parameters on the flux linkage of one phase of the stator winding depending on the excitation current I. The influence of each parameter is analyzed via the Sobol indices. With this analysis, we can determine the most influential parameters for each state of magnetization (according to the level of I) and investigate where the characterization process of the B(H) curve should focus to improve the accuracy of the computed flux linkage.
International Journal of Computer Mathematics, 2014
In this paper, we present a framework to deal with uncertainty quantification in case where the r... more In this paper, we present a framework to deal with uncertainty quantification in case where the ranges of variability of the random parameters are ill-known. Namely the physical properties of the corrosion product (magnetite) which frequently clogs the tube support plate of steam generator, which is inaccessible in nuclear power plants. The methodology is based on Polynomial Chaos (PC) for the direct approach and on Bayesian inference for the inverse approach. The direct Non-Intrusive Spectral Projection (NISP) method is first employed by considering prior probability densities and therefore constructing a PC surrogate model of the large-scale NDT finite element model. To face the prohibitive computational cost underlying the high dimensional random space, an adaptive sparse grid technique is applied on NISP resulting in drastic time reduction. The PC surrogate model, with reduced dimensionality, is used as a forward model in the Bayesian procedure. The posterior probability densities are then identified by inferring from few noisy experimental data. We demonstrate effectiveness of the approach by identifying the most influential parameter in the clogging detection as well as a variability range reduction.
COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, 2020
Purpose This paper aims to go deeper on the analysis of the shaft voltage of large turbogenerator... more Purpose This paper aims to go deeper on the analysis of the shaft voltage of large turbogenerators. The main interest of this study is the investigation process developed. Design/methodology/approach The analysis of the shaft voltage because of several defects is based on a two-dimensional (2D) finite element modeling. This 2D finite element model is used to determine the shaft voltage because of eccentricities or rotor short-circuit. Findings Dynamic eccentricities and rotor short circuit do not have an inherent impact on the shaft voltage. Circulating currents in the stator winding because of defects impact the shaft voltage. Originality/value The original value of this paper is the investigation process developed. This study proposes to quantify the impact of a smooth stator and then to explore the contribution of the real stator winding on the shaft voltage.
The Non-Intrusive Spectral Projection (NISP) method is widely used for uncertainty quantification... more The Non-Intrusive Spectral Projection (NISP) method is widely used for uncertainty quantification in stochastic models. The determination of the expansion of the solution on the polynomial chaos requires the computation of multidimensional integrals. An automatic adaptive algorithm based on nested sparse grids has been developed to evaluate those integrals. The adapted algorithm takes into account the weight of each random variable with respect to the output of the model. To achieve that it constructs anisotropic sparse grid of the mean, leading to a reduction of the number of numerical simulations. Furthermore, the spectral form of the solution is explicitly identified from the constructed quadrature scheme. Numerical results obtained on an industrial application in NDT demonstrate the efficiency of the proposed method.
In this paper, we present a framework to deal with uncertainty quantification in case where the r... more In this paper, we present a framework to deal with uncertainty quantification in case where the ranges of variability of the random parameters are ill-known. Namely the physical properties of the corrosion product (magnetite) which frequently clogs the tube support plate of steam generator, which is inaccessible in nuclear power plants. The methodology is based on Polynomial Chaos (PC) direct approaches and on Bayesian inference for inverse problems. The direct Non Intrusive Spectral Projection (NISP) method is first employed by considering prior probability densities and therefore construct a PC surrogate model of the large-scale NDT finite element model. To face the prohibitive computational cost underlying the high dimensional random space, the adaptive sparse grid technique is applied on NISP resulting in a significant time reduction. The PC surrogate model, with reduced dimensionality, is used as a forward model in the Bayesian procedure. The posterior probability densities are then identified by inferring from few noisy experimental data. We demonstrate the effectiveness of the approach on the identification the permeability and conductivity of the magnetite using Sax ratio measurements.
This study presents a strategy for estimating the states and the load torque to implement a feedb... more This study presents a strategy for estimating the states and the load torque to implement a feedback linearisation controller for induction motor drives. The multivariable control is carried out using input-output linearisation feedback law in order to track profiles of the rotational speed and the rotor flux amplitude. The unknown load torque is compensated by an estimator based on the speed error. The state estimation requires only the measurements of the stator voltagescurrents. The estimation method is not invasive as no mechanical sensors are needed. Experimental platform equipped with sensors at the load side, for measuring the speed and the torque of the motor driven by the Opal-RT real-time system, was implemented to verify the accuracy of the proposed estimation method to implement the multivariable control.
This paper presents bearings faults detection and isolation system for a wind energy conversion s... more This paper presents bearings faults detection and isolation system for a wind energy conversion system (WECS). For this, and contrary to the traditional methods often used and based on the frequency and/or the vibration analysis of generator signals, this novel approach is based on the temporal analysis of electrical signals (current or voltage) of the generator. The method is based on the observer scheme, composed of a time-varying Kalman filter and the strategy of the mean-residual to generate new residual capable to detect and quantify all bearings faults types. The proposed system has been validated on signals of a doubly-fed induction generator and the simulation results approve its efficiency.
This study presents a new strategy for estimating the states (rotor flux and speed) and the load ... more This study presents a new strategy for estimating the states (rotor flux and speed) and the load torque to implement a multivariable controller for a sensorless three-phase squirrel-cage induction machine in wind energy conversion systems. The multivariable control is carried out using input–output feedback law and its objective is to track profiles of the rotational speed and the rotor flux amplitude. The state estimation considerably improves the performance of rotor flux based model reference adaptive system in the variable speed region of operation. The technique uses Kalman filter as a rotor flux observer and an artificial neural network adaption mechanism to estimate the rotor speed. The state estimation requires only the measurements of the stator voltages and currents. The estimation method, for both states and torque, is not invasive as no mechanical sensors are needed. The wind energy conversion system and the proposed control-estimation techniques are simulated in Matlab/ Simulink software platform and tested using the OPAL-RT real-time simulator (OP5600) to verify the accuracy of the proposed control-estimation method.
he approximation of a complex function by an Artificial Neural Networks (ANN) of Radial basis Fun... more he approximation of a complex function by an Artificial Neural Networks (ANN) of Radial basis Function (NRF) conducts to large size architectures (a considerable number of neurons in the hidden layer) which minimize the quality of the network generation. This paper develops and implements an algorithm based on the Newton’s method for learning and searching for an optimal structure of a radial basis network. The algorithm reduces automatically the number of neurons in the hidden layer of the ANN and also reaches the minimal architecture without deteriorating the learning error. Tovalidate the algorithm, simulation of filtering noise from a noisy sinusoidal signal has been performed using MATLAB/SIMULINK. Satisfying results have been obtained and application as a filter for fault detection in a Wind Energy Conversion System (WECS) is intended.
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