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The topic of microgrids (MGs) is a fast-growing and very promising field of research in terms of energy production quality, pollution reduction and sustainable development. Moreover, MGs are, above all, designed to considerably improve the autonomy, sustainability, and reliability of future electrical distribution grid. At the same time, aspects of MGs energy management, taking into consideration distribution generation systems, energy storage devices, electric vehicles, and consumption components have been widely investigated. Besides, grid architectures including DC, AC, or hybrid power generation systems, energy dispatching problems modelling, operating modes (islanded or grid connected), MGs sizing, simulations and problems solving optimization approaches, and other aspects, have been raised as topics of great interest for both electrical and computer sciences research communities. Furthermore, the United Nations Framework Convention on Climate Change and government policies and incentives have paved the way to massive electric vehicle (EV) deployment. Hence, several research studies have been conducted to investigate the integration of EVs in national power grid and future MGs. Specifically, EV charging stations’ bi-directional power flow control and energy management have been considerably explored. These issues index challenging research topics, which are in most cases still under progress. This paper gives an overview of MGs technology advancement in recent decades, taking into consideration distributed energy generation (DER), energy storage systems (ESS), EVs, and loads. It reviews the main MGs architecture, operating modes, sizing and energy management systems (EMS) and EVs integration.
Oussama Ouramdane; Elhoussin Elbouchikhi; Yassine Amirat; Ehsan Sedgh Gooya. Optimal Sizing and Energy Management of Microgrids with Vehicle-to-Grid Technology: A Critical Review and Future Trends. Energies 2021, 14, 4166 .
AMA StyleOussama Ouramdane, Elhoussin Elbouchikhi, Yassine Amirat, Ehsan Sedgh Gooya. Optimal Sizing and Energy Management of Microgrids with Vehicle-to-Grid Technology: A Critical Review and Future Trends. Energies. 2021; 14 (14):4166.
Chicago/Turabian StyleOussama Ouramdane; Elhoussin Elbouchikhi; Yassine Amirat; Ehsan Sedgh Gooya. 2021. "Optimal Sizing and Energy Management of Microgrids with Vehicle-to-Grid Technology: A Critical Review and Future Trends." Energies 14, no. 14: 4166.
In the last years, predictive maintenance has gained a central position in condition-based maintenance tasks planning. Machine learning approaches have been very successful in simplifying the construction of prognostic models for health assessment based on available historical labeled data issued from similar systems or specific physical models. However, if the collected samples suffer from lack of labels (small labeled dataset or not enough samples), the process of generalization of the learning model on the dataset as well as on the newly arrived samples (application) can be very difficult. In an attempt to overcome such drawbacks, a new deep supervised learning approach is introduced in this paper. The proposed approach aims at extracting and learning important patterns even from a small amount of data in order to produce more general health estimator. The algorithm is trained online based on local receptive field theories of extreme learning machines using data issued from a propulsion system simulator. Compared to extreme learning machine variants, the new algorithm shows a higher level of accuracy in terms of approximation and generalization under several training paradigms.
Tarek Berghout; Leïla-Hayet Mouss; Toufik Bentrcia; Elhoussin Elbouchikhi; Mohamed Benbouzid. A deep supervised learning approach for condition-based maintenance of naval propulsion systems. Ocean Engineering 2020, 221, 108525 .
AMA StyleTarek Berghout, Leïla-Hayet Mouss, Toufik Bentrcia, Elhoussin Elbouchikhi, Mohamed Benbouzid. A deep supervised learning approach for condition-based maintenance of naval propulsion systems. Ocean Engineering. 2020; 221 ():108525.
Chicago/Turabian StyleTarek Berghout; Leïla-Hayet Mouss; Toufik Bentrcia; Elhoussin Elbouchikhi; Mohamed Benbouzid. 2020. "A deep supervised learning approach for condition-based maintenance of naval propulsion systems." Ocean Engineering 221, no. : 108525.
Today, pitch-controlled variable speed wind turbines (WTs) are the most installed Wind Energy Conversion (WEC) systems. They mainly use two types of generators: the permanent magnet synchronous generator (PMSG) and the double-fed induction generator (DFIG). In this paper, the overall configuration of DFIG-based WEC systems is reviewed and its control strategy is experimentally implemented using dSPACE DS1104 controller board. In this context, emphasis is placed on active power transfer management, reactive power compensation, and sinusoidal current injection into the main grid to improve power quality. The built lab-scale prototype allows validating different subsystems operation and demonstrating DFIG-based WEC capabilities. This paper specifically provides a thorough and consistent step-by-step modeling and control design methodology for a DFIG-based WEC simulation and experimentation platform that could be used for education and research addressing the wind energy conversion timely topic.
Elhoussin Elbouchikhi; Gilles Feld; Yassine Amirat; Mohamed Benbouzid; Franck Le Gall. Design and experimental implementation of a wind energy conversion platform with education and research capabilities. Computers & Electrical Engineering 2020, 85, 1 .
AMA StyleElhoussin Elbouchikhi, Gilles Feld, Yassine Amirat, Mohamed Benbouzid, Franck Le Gall. Design and experimental implementation of a wind energy conversion platform with education and research capabilities. Computers & Electrical Engineering. 2020; 85 ():1.
Chicago/Turabian StyleElhoussin Elbouchikhi; Gilles Feld; Yassine Amirat; Mohamed Benbouzid; Franck Le Gall. 2020. "Design and experimental implementation of a wind energy conversion platform with education and research capabilities." Computers & Electrical Engineering 85, no. : 1.
Neodymium-boron (NdFeB) permanent magnets (PMs) have been widely studied in the past years since they became the material of choice in permanent magnet synchronous machines (PMSMs). Although NdFeB PMs have a better energy density than other types of magnets and are cost-effective, their magnetization is very sensitive to the PMSM operating conditions, in particular temperature, where the irreversible demagnetization degree increases over time. Therefore, it is important to characterize and diagnose demagnetization at an early stage. In this context, this paper proposes a two-step analysis study dealing with both uniform and partial demagnetization. A 2D finite element method-based (FEM) approach is used for demagnetization characterization, and then a PMSM motor current signature analysis (MCSA) approach, based on fast Fourier transform (FFT), is considered where fault cases harmonics are considered as faults indices to detect demagnetization. In some situations, the proposed two-step approach achieved results that clearly allow distinguishing and characterizing demagnetization. Indeed, a local demagnetization introduces specific sub-harmonics while a uniform demagnetization leads to the current amplitude increase for a given torque.
Manel Krichen; Elhoussin Elbouchikhi; Naourez Benhadj; Mohamed Chaieb; Mohamed Benbouzid; Rafik Neji. Motor Current Signature Analysis-Based Permanent Magnet Synchronous Motor Demagnetization Characterization and Detection. Machines 2020, 8, 35 .
AMA StyleManel Krichen, Elhoussin Elbouchikhi, Naourez Benhadj, Mohamed Chaieb, Mohamed Benbouzid, Rafik Neji. Motor Current Signature Analysis-Based Permanent Magnet Synchronous Motor Demagnetization Characterization and Detection. Machines. 2020; 8 (3):35.
Chicago/Turabian StyleManel Krichen; Elhoussin Elbouchikhi; Naourez Benhadj; Mohamed Chaieb; Mohamed Benbouzid; Rafik Neji. 2020. "Motor Current Signature Analysis-Based Permanent Magnet Synchronous Motor Demagnetization Characterization and Detection." Machines 8, no. 3: 35.
This paper studies the grid-synchronization problem of three-phase system. Second-order adaptive filters are a popular tool for grid-synchronization. In this context, reduced-order generalized integrator has attracted some attention in recent time. However, existing implementations cannot control directly the closed-loop poles (real and imaginary) of reduced-order generalized integrator. To overcome this limitation, this paper proposes a novel reduced-order generalized integrator structure. To make the proposed technique frequency adaptive, an open-loop frequency estimation technique is also used. Comparative performance analysis are provided over two other advanced and recently proposed techniques. Results demonstrate the suitability and effectiveness of the proposed technique.
Hafiz Ahmed; Samet Biricik; Elhoussin Elbouchikhi; Mohamed Benbouzid. Adaptive Filtering-Based Pseudo Open-Loop Three-Phase Grid-Synchronization Technique. Energies 2020, 13, 1 .
AMA StyleHafiz Ahmed, Samet Biricik, Elhoussin Elbouchikhi, Mohamed Benbouzid. Adaptive Filtering-Based Pseudo Open-Loop Three-Phase Grid-Synchronization Technique. Energies. 2020; 13 (11):1.
Chicago/Turabian StyleHafiz Ahmed; Samet Biricik; Elhoussin Elbouchikhi; Mohamed Benbouzid. 2020. "Adaptive Filtering-Based Pseudo Open-Loop Three-Phase Grid-Synchronization Technique." Energies 13, no. 11: 1.
Most electrical machines and drive signals are non-Gaussian and are highly nonlinear in nature. A useful set of techniques to examine such signals relies on higher-order statistics (HOS) spectral representations. They describe statistical dependencies of frequency components that are neglected by traditional spectral measures, namely the power spectrum (PS). One of the most used HOS is the bispectrum where examining higher-order correlations should provide further details and information about the conditions of electric machines and drives. In this context, the stator currents of electric machines are of particular interest because they are periodic, nonlinear, and cyclostationary. This current is, therefore, well adapted for analysis using bispectrum in the designing of an efficient condition monitoring method for electric machines and drives. This paper is, therefore, proposing a bispectrum-based diagnosis method dealing the with tidal stream turbine (TST) rotor blades biofouling issue, which is a marine environment natural process responsible for turbine rotor unbalance. The proposed bispectrum-based diagnosis method is verified using experimental data provided from a permanent magnet synchronous generator (PMSG)-based TST experiencing biofouling emulated by attachment on the turbine blade. Based on the achieved results, it can be concluded that the proposed diagnosis method has been very successful. Indeed, biofouling imbalance-related frequencies are clearly identified despite marine environmental nuisances (turbulences and waves).
Lotfi Saidi; Mohamed Benbouzid; Demba Diallo; Yassine Amirat; Elhoussin Elbouchikhi; Tianzhen Wang. Higher-Order Spectra Analysis-Based Diagnosis Method of Blades Biofouling in a PMSG Driven Tidal Stream Turbine. Energies 2020, 13, 2888 .
AMA StyleLotfi Saidi, Mohamed Benbouzid, Demba Diallo, Yassine Amirat, Elhoussin Elbouchikhi, Tianzhen Wang. Higher-Order Spectra Analysis-Based Diagnosis Method of Blades Biofouling in a PMSG Driven Tidal Stream Turbine. Energies. 2020; 13 (11):2888.
Chicago/Turabian StyleLotfi Saidi; Mohamed Benbouzid; Demba Diallo; Yassine Amirat; Elhoussin Elbouchikhi; Tianzhen Wang. 2020. "Higher-Order Spectra Analysis-Based Diagnosis Method of Blades Biofouling in a PMSG Driven Tidal Stream Turbine." Energies 13, no. 11: 2888.
As an emerging technology to harness the marine current energy, tidal stream turbine (TST) systems have been developed due to high predictability and energy density in tidal current resources. However, considering that various challenges such as swell disturbances, unknown disturbances, or parameter uncertainties may deteriorate the system performance, it is interesting to investigate alternative control strategies to the conventional proportional-integral (PI) controls. In this paper, the active disturbance rejection control (ADRC) approach is proposed to replace PI controllers in the conventional generator-side control scheme. In this approach, two ADRC schemes (cascaded and second-order ADRC strategies) are respectively applied and compared to achieve MPPT under current velocity and turbine torque disturbances. Performances of the proposed ADRC approaches are compared to PI and sliding mode control strategies. Energy production during swell wave disturbance is also evaluated under these control strategies. The comparisons show that the cascaded ADRC has better performance than the second-order approach. Moreover, the cascaded ADRC is tested under parameter variations to evaluate its robustness. The carried out simulation-based comparative study shows the effectiveness and advantages of the cascaded ADRC strategy over conventional PI controller in terms of fast convergence, overshoots elimination, and improved robustness under disturbances and parameter uncertainties.
Zhibin Zhou; Seifeddine Ben Elghali; Mohamed Benbouzid; Yassine Amirat; Elhoussin Elbouchikhi; Gilles Feld. Tidal stream turbine control: An active disturbance rejection control approach. Ocean Engineering 2020, 202, 107190 .
AMA StyleZhibin Zhou, Seifeddine Ben Elghali, Mohamed Benbouzid, Yassine Amirat, Elhoussin Elbouchikhi, Gilles Feld. Tidal stream turbine control: An active disturbance rejection control approach. Ocean Engineering. 2020; 202 ():107190.
Chicago/Turabian StyleZhibin Zhou; Seifeddine Ben Elghali; Mohamed Benbouzid; Yassine Amirat; Elhoussin Elbouchikhi; Gilles Feld. 2020. "Tidal stream turbine control: An active disturbance rejection control approach." Ocean Engineering 202, no. : 107190.
Flywheel is a promising energy storage system for domestic application, uninterruptible power supply, traction applications, electric vehicle charging stations, and even for smart grids. In fact, recent developments in materials, electrical machines, power electronics, magnetic bearings, and microprocessors offer the possibility to consider flywheels as a competitive option for electric energy storage, which can be of great interest for domestic applications in the near future. In this paper, a grid-tied flywheel-based energy storage system (FESS) for domestic application is investigated with special focus on the associated power electronics control and energy management. In particular, the overall PMSM-based flywheel configuration is reviewed and a controlling strategy was experimentally implemented using DS1104 controller board from dSPACE. Two case studies were considered for power peak shaving and power backup at domestic level. A lab-scale prototype was built to validate the proposal. The achieved results are presented and discussed to demonstrate the possibilities offered by such an energy storage system for domestic application.
Elhoussin Elbouchikhi; Yassine Amirat; Gilles Feld; Mohamed Benbouzid; Zhibin Zhou. A Lab-scale Flywheel Energy Storage System: Control Strategy and Domestic Applications. Energies 2020, 13, 653 .
AMA StyleElhoussin Elbouchikhi, Yassine Amirat, Gilles Feld, Mohamed Benbouzid, Zhibin Zhou. A Lab-scale Flywheel Energy Storage System: Control Strategy and Domestic Applications. Energies. 2020; 13 (3):653.
Chicago/Turabian StyleElhoussin Elbouchikhi; Yassine Amirat; Gilles Feld; Mohamed Benbouzid; Zhibin Zhou. 2020. "A Lab-scale Flywheel Energy Storage System: Control Strategy and Domestic Applications." Energies 13, no. 3: 653.
Muhammad F. Zia; Mohamed Benbouzid; Elhoussin Elbouchikhi; S. M. Muyeen; Kuaanan Techato; Josep M. Guerrero. Microgrid Transactive Energy: Review, Architectures, Distributed Ledger Technologies, and Market Analysis. IEEE Access 2020, 8, 19410 -19432.
AMA StyleMuhammad F. Zia, Mohamed Benbouzid, Elhoussin Elbouchikhi, S. M. Muyeen, Kuaanan Techato, Josep M. Guerrero. Microgrid Transactive Energy: Review, Architectures, Distributed Ledger Technologies, and Market Analysis. IEEE Access. 2020; 8 ():19410-19432.
Chicago/Turabian StyleMuhammad F. Zia; Mohamed Benbouzid; Elhoussin Elbouchikhi; S. M. Muyeen; Kuaanan Techato; Josep M. Guerrero. 2020. "Microgrid Transactive Energy: Review, Architectures, Distributed Ledger Technologies, and Market Analysis." IEEE Access 8, no. : 19410-19432.
With the advancements in power electronic devices, the increasing use of DC loads, DC renewable generation sources and battery storage systems, and no reactive power and frequency stability issues, DC microgrids are increasingly gaining attention in both academia and industry. In this paper, a grid-connected DC microgrid is considered, which consists of a PV system and a Li-ion battery. DC microgrids optimal operation requires battery degradation cost modeling and demand response incentive for active consumers’ participation to be addressed in detail. Therefore, a practical degradation cost model for a Li-ion battery is developed to optimize battery scheduling and achieve its realistic operational cost. Apart from energy price, scheduled islanding responsive demand response incentive is also introduced to encourage customers to shift load during scheduled grid-tie line maintenance. Levelized cost of energy of PV system is calculated for both hot and cold climate regions. Optimal operation of DC microgrid cannot be achieved without considering nodal voltages and system losses. Hence, network constraints are also included in the proposed model. Extensive numerical simulations are carried out to prove the effectiveness of the proposed approach. The achieved results would aid in DC microgrids adoption planning that would expectedly replace traditional AC grids in the future.
Muhammad Fahad Zia; Elhoussin Elbouchikhi; Mohamed Benbouzid. Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations. Applied Energy 2019, 237, 695 -707.
AMA StyleMuhammad Fahad Zia, Elhoussin Elbouchikhi, Mohamed Benbouzid. Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations. Applied Energy. 2019; 237 ():695-707.
Chicago/Turabian StyleMuhammad Fahad Zia; Elhoussin Elbouchikhi; Mohamed Benbouzid. 2019. "Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations." Applied Energy 237, no. : 695-707.
This paper proposes a new approach for inverter-fed induction motor stator faults detection under closed-loop control. These faults, generally, start with interturns short-circuit and can evolve to phase-to-phase or phase-to-ground faults, leading to stator currents unbalance. In the considered application, the stator windings are supplied by a static converter for the control of the speed and the rotor flux of the motor. The unbalance fault has been artificially created through additional resistance in series with one phase of the stator windings. The proposed diagnosis approach is based on the computation of the symmetrical components (SCs) of the stator currents. The supply fundamental frequency and the three-phase phasors are estimated based on the maximum likelihood estimator (MLE). Then, the generalized likelihood ratio test (GLRT) is applied for unbalance fault detection. Simulation and experimental results on a 1.5-kW induction motor illustrate the effectiveness of the proposed approach, leading to an effective diagnosis procedure for stator faults in inverter-fed induction motor under steady state and closed-loop operation.
Elhoussin Elbouchikhi; Yassine Amirat; Gilles Feld; Mohamed Benbouzid. Generalized Likelihood Ratio Test Based Approach for Stator-Fault Detection in a PWM Inverter-Fed Induction Motor Drive. IEEE Transactions on Industrial Electronics 2018, 66, 6343 -6353.
AMA StyleElhoussin Elbouchikhi, Yassine Amirat, Gilles Feld, Mohamed Benbouzid. Generalized Likelihood Ratio Test Based Approach for Stator-Fault Detection in a PWM Inverter-Fed Induction Motor Drive. IEEE Transactions on Industrial Electronics. 2018; 66 (8):6343-6353.
Chicago/Turabian StyleElhoussin Elbouchikhi; Yassine Amirat; Gilles Feld; Mohamed Benbouzid. 2018. "Generalized Likelihood Ratio Test Based Approach for Stator-Fault Detection in a PWM Inverter-Fed Induction Motor Drive." IEEE Transactions on Industrial Electronics 66, no. 8: 6343-6353.
This paper investigates the use of instantaneous symmetrical components (ISCs) for mechanical faults detection in inverter-fed induction motors under closed-loop control. The proposed fault detection approach is based on the computation of the ISCs of the stator currents. The positive sequence power spectral density (PSD) is estimated using ESPRIT and least squares (LS). Then, mechanical fault detection is considered as a binary hypothesis test and solved using the generalized likelihood ratio test (GLRT). Both stator currents and the modulating signals issued from the control-loops are demonstrated to be efficient for fault detection. Simulation results on an analytical model of an inverter-fed induction motor illustrate the effectiveness of the proposed approach, leading to an effective fault detection procedure for load torque oscillation in inverter-fed induction motor under closed-loop operation.
Elhoussin Elbouchikhi; Vincent Choqueuse; Gilles Feld; Yassine Amirat; Mohamed Benbouzid. A symmetrical components-based load oscillation detection method for closed-loop controlled induction motors. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society 2017, 8047 -8052.
AMA StyleElhoussin Elbouchikhi, Vincent Choqueuse, Gilles Feld, Yassine Amirat, Mohamed Benbouzid. A symmetrical components-based load oscillation detection method for closed-loop controlled induction motors. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. 2017; ():8047-8052.
Chicago/Turabian StyleElhoussin Elbouchikhi; Vincent Choqueuse; Gilles Feld; Yassine Amirat; Mohamed Benbouzid. 2017. "A symmetrical components-based load oscillation detection method for closed-loop controlled induction motors." IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society , no. : 8047-8052.
Motor current signature analysis (MCSA) is a well-proven technique for electrical and mechanical faults detection in induction motors. The appearance of stator current components or increase of magnitude of some components at characteristic frequencies indicates a motor fault condition. In this paper, we propose a new MCSA fault detector based on a matched subspace technique. The proposed detector consists of three steps. First, the influence of the fundamental supply frequency is removed from the current signal using an interference cancellation technique based on oblique projection. Then, the fault-related frequency is estimated from the interference-free signal using the maximum likelihood principle. Finally, the fault detection is performed using a generalized likelihood ratio test. Simulation and experimental results illustrate the effectiveness of the proposed approach for eccentricity fault, bearing faults, and broken rotor bars detection.
Elhoussin Elbouchikhi; Vincent Choqueuse; Francois Auger; Mohamed El Hachemi Benbouzid. Motor Current Signal Analysis Based on a Matched Subspace Detector. IEEE Transactions on Instrumentation and Measurement 2017, 66, 3260 -3270.
AMA StyleElhoussin Elbouchikhi, Vincent Choqueuse, Francois Auger, Mohamed El Hachemi Benbouzid. Motor Current Signal Analysis Based on a Matched Subspace Detector. IEEE Transactions on Instrumentation and Measurement. 2017; 66 (12):3260-3270.
Chicago/Turabian StyleElhoussin Elbouchikhi; Vincent Choqueuse; Francois Auger; Mohamed El Hachemi Benbouzid. 2017. "Motor Current Signal Analysis Based on a Matched Subspace Detector." IEEE Transactions on Instrumentation and Measurement 66, no. 12: 3260-3270.
This paper deals with the modeling and simulation of a permanent magnet synchronous generator (PMSG)-based marine current turbine (MCT) under faulty rectifier conditions. The modeling of the generator is established in the synchronous rotating d-q reference frame. The control of the speed, the d-axis current, and the q-axis current are achieved using proportional integral (PI) correctors. The faulty mode deals with the study of single and multiple open-switch damages appearing in the pulse width modulation (PWM) power rectifier. Simulations are carried out to highlight the proposed PMSG-based MCT performance in both cases using MATLAB/Simulink environment.
Sana Toumi; Seifeddine Benelghali; Mohamed Trabelsi; Elhoussin Elbouchikhi; Yassine Amirat; Mohamed Benbouzid; Mohamed Faouzi Mimouni. Modeling and Simulation of a PMSG-based Marine Current Turbine System under Faulty Rectifier Conditions. Electric Power Components and Systems 2017, 45, 715 -725.
AMA StyleSana Toumi, Seifeddine Benelghali, Mohamed Trabelsi, Elhoussin Elbouchikhi, Yassine Amirat, Mohamed Benbouzid, Mohamed Faouzi Mimouni. Modeling and Simulation of a PMSG-based Marine Current Turbine System under Faulty Rectifier Conditions. Electric Power Components and Systems. 2017; 45 (7):715-725.
Chicago/Turabian StyleSana Toumi; Seifeddine Benelghali; Mohamed Trabelsi; Elhoussin Elbouchikhi; Yassine Amirat; Mohamed Benbouzid; Mohamed Faouzi Mimouni. 2017. "Modeling and Simulation of a PMSG-based Marine Current Turbine System under Faulty Rectifier Conditions." Electric Power Components and Systems 45, no. 7: 715-725.
This paper focuses on rolling elements bearing fault detection in induction machines based on stator currents analysis. Specifically, it proposes to process the stator currents using the Hilbert-Huang transform. This approach relies on two steps: empirical mode decomposition and Hilbert transform. The empirical mode decomposition is used in order to estimate the intrinsic mode functions (IMFs). These IMFs are assumed to be mono-component signals and can be processed using demodulation technique. Afterward, the Hilbert transform is used to compute the instantaneous amplitude (IA) and instantaneous frequency (IF) of these IMFs. The analysis of the IA and IF allows identifying fault signature that can be used for more accurate diagnosis. The proposed approach is used for bearing fault detection in induction machines at several fault degrees. The effectiveness of the proposed approach is verified by a series of simulation and experimental tests corresponding to different bearing fault conditions. The fault severity is assessed based on the IMFs energy and the variance of the IA and IF of each IMF.
El Houssin El Bouchikhi; Vincent Choqueuse; Yassine Amirat; Mohamed El Hachemi Benbouzid; Sylvie Turri. An Efficient Hilbert–Huang Transform-Based Bearing Faults Detection in Induction Machines. IEEE Transactions on Energy Conversion 2017, 32, 401 -413.
AMA StyleEl Houssin El Bouchikhi, Vincent Choqueuse, Yassine Amirat, Mohamed El Hachemi Benbouzid, Sylvie Turri. An Efficient Hilbert–Huang Transform-Based Bearing Faults Detection in Induction Machines. IEEE Transactions on Energy Conversion. 2017; 32 (2):401-413.
Chicago/Turabian StyleEl Houssin El Bouchikhi; Vincent Choqueuse; Yassine Amirat; Mohamed El Hachemi Benbouzid; Sylvie Turri. 2017. "An Efficient Hilbert–Huang Transform-Based Bearing Faults Detection in Induction Machines." IEEE Transactions on Energy Conversion 32, no. 2: 401-413.
Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes.
Elhoussin Elbouchikhi; Vincent Choqueuse; Mohamed Benbouzid. Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation. ISA Transactions 2016, 63, 413 -424.
AMA StyleElhoussin Elbouchikhi, Vincent Choqueuse, Mohamed Benbouzid. Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation. ISA Transactions. 2016; 63 ():413-424.
Chicago/Turabian StyleElhoussin Elbouchikhi; Vincent Choqueuse; Mohamed Benbouzid. 2016. "Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation." ISA Transactions 63, no. : 413-424.
The main objective of this paper is to detect faults in induction machines using a condition monitoring architecture based on stator current measurements. Two types of fault are considered: bearing and broken rotor bars faults. The proposed architecture is based on high-resolution spectral analysis techniques also known as subspace techniques. These frequency estimation techniques allow to separate frequency components including frequencies close to the fundamental one. These frequencies correspond to fault sensitive frequencies. Once frequencies are estimated, their corresponding amplitudes are obtained by using the least squares estimator. Then, a fault severity criterion is derived from the amplitude estimates. The proposed methods were tested using experimental stator current signals issued from two induction motors with the considered faults. The experimental results show that the proposed architecture has the ability to efficiently and cost-effectively detect faults and identify their severity.
Youness Trachi; El Houssin El Bouchikhi; Vincent Choqueuse; Mohamed El Hachemi Benbouzid. Induction Machines Fault Detection Based on Subspace Spectral Estimation. IEEE Transactions on Industrial Electronics 2016, 63, 5641 -5651.
AMA StyleYouness Trachi, El Houssin El Bouchikhi, Vincent Choqueuse, Mohamed El Hachemi Benbouzid. Induction Machines Fault Detection Based on Subspace Spectral Estimation. IEEE Transactions on Industrial Electronics. 2016; 63 (9):5641-5651.
Chicago/Turabian StyleYouness Trachi; El Houssin El Bouchikhi; Vincent Choqueuse; Mohamed El Hachemi Benbouzid. 2016. "Induction Machines Fault Detection Based on Subspace Spectral Estimation." IEEE Transactions on Industrial Electronics 63, no. 9: 5641-5651.