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3137 3146 64 11 ; S ; © 2015 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. [EN] The discrete wavelet transform (DWT) has attracted a rising interest in recent years to monitor the condition of rotating electrical machines in transient regime, because it can reveal the time-frequency behavior of the current's components associated to fault conditions. Nevertheless, the implementation of the wavelet transform (WT), especially on embedded or low-power devices, faces practical problems, such as the election of the mother wavelet, the tuning of its parameters, the coordination between the sampling frequency and the levels of the transform, and the construction of the bank of wavelet filters, with highly different bandwidths that constitute the core of the DWT. In this paper, a diagnostic system using the harmonic WT is proposed, which can alleviate these practical problems because it is built using a single fast Fourier transform of one phase's current. The harmonic wavelet was conceived to perform musical analysis, hence its name, and it has spread into many fields, but, to the best of the authors' knowledge, it has not been applied before to perform fault diagnosis of rotating electrical machines in transient regime using the stator current. The simplicity and performance of the proposed approach are assessed by comparison with other types of WTs, and it has been validated with the experimental diagnosis of a 3.15-MW induction motor with broken bars. This work was supported by the Spanish Ministerio de Ciencia e Innovacion through the Programa Nacional de Proyectos de Investigacion Fundamental under Project DPI2011-23740. The Associate Editor coordinating the review process was Dr. Ruqiang ...

432 440 66 3 ; S ; [EN] Transient-based methods for fault diagnosis of induction machines (IMs) are attracting a rising interest, due to their reliability and ability to adapt to a wide range of IM's working conditions. These methods compute the time-frequency (TF) distribution of the stator current, where the patterns of the related fault components can be detected. A significant amount of recent proposals in this field have focused on improving the resolution of the TF distributions, allowing a better discrimination and identification of fault harmonic components. Nevertheless, as the resolution improves, computational requirements (power computing and memory) greatly increase, restricting its implementation in low-cost devices for performing on-line fault diagnosis. To address these drawbacks, in this paper, the use of the short-frequency Fourier transform (SFFT) for fault diagnosis of induction machines working under transient regimes is proposed. The SFFT not only keeps the resolution of traditional techniques, such as the short-time Fourier transform, but also achieves a drastic reduction of computing time and memory resources, making this proposal suitable for on-line fault diagnosis. This method is theoretically introduced and experimentally validated using a laboratory test bench. This work was supported by the Spanish Ministerio de Economia y Competitividad in the framework of the Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, under Project DPI2014-60881-R. The Associate Editor coordinating the review process was Dr. Edoardo Fiorucci. Burriel-Valencia, J.; Puche-Panadero, R.; Martinez-Roman, J.; Sapena-Bañó, Á.; Pineda-Sanchez, M. (2017). Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime. IEEE Transactions on Instrumentation and Measurement. 66(3):432-440. doi:10.1109/TIM.2016.2647458

1 16 13 21 ; S García-Sánchez, T., Muñoz-Benavente, I., Gómez-Lázaro, E., & Fernández-Guillamón, A. (2020). Modelling Types 1 and 2 Wind Turbines Based on IEC 61400-27-1: Transient Response under Voltage Dips. Energies, 13(16), 4078. doi:10.3390/en13164078 Muhsen, H., Al-Kouz, W., & Khan, W. (2019). Small Wind Turbine Blade Design and Optimization. Symmetry, 12(1), 18. doi:10.3390/sym12010018 Anelion SW 3.5 GThttps://www.wind-turbine-models.com/turbines/950-anelion-sw-3.5-gt ; Das, K., Hansen, A. D., & Sørensen, P. E. (2016). Understanding IEC standard wind turbine models using SimPowerSystems. Wind Engineering, 40(3), 212-227. doi:10.1177/0309524x16642058 ; [EN] Currently, wind power is the fastest-growing means of electricity generation in the world. To obtain the maximum efficiency from the wind energy conversion system, it is important that the control strategy design is carried out in the best possible way. In fact, besides regulating the frequency and output voltage of the electrical signal, these strategies should also extract energy from wind power at the maximum level of efficiency. With advances in micro-controllers and electronic components, the design and implementation of efficient controllers are steadily improving. This paper presents a maximum power point tracking controller scheme for a small wind energy conversion system with a variable speed permanent magnet synchronous generator. With the controller, the system extracts optimum possible power from the wind speed reaching the wind turbine and feeds it to the grid at constant voltage and frequency based on the AC-DC-AC conversion system. A MATLAB/SimPowerSystems environment was used to carry out the simulations of the system. Simulation results were analyzed under variable wind speed and load conditions, exhibiting the performance of the proposed controller. It was observed that the controllers can extract maximum power and regulate the voltage and frequency under such variable conditions. Extensive results are included in the ...

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. ; [EN] While wind turbine (WT) power capacities continue to increase and new offshore developments are being deployed, operation and maintenance (O&M) costs continue to rise, becoming the center of attention in the wind energy sector. The electric generator is among the top three contributors to failure rates and downtime of WTs, where the doubly fed induction generator (DFIG) is the dominant technology among variable speed WTs. Thus, the early detection of generator faults, which can be achieved through predictive maintenance, is vital in order to reduce O&M costs. The goal of this paper is to analyze a long-term monitoring campaign of an in-service WT equipped with a DFIG. A novel method named the harmonic order tracking analysis is used with two main objectives: first, to facilitate the data interpretation for non-trained maintenance personnel, and second, to reduce the amount of data that must be stored and transferred for the diagnosis of the DFIG. This method is applied and validated for the first time on an operating WT. ; This work was supported in part by the Agreement signed between the UCLM and the Council of Albacete to promote research in the Campus of Albacete, and in part by the European Union Horizon 2020 Research and Innovation Programme through the Marie Sklodowska-Curie Grant (AWESOME Project) under Grant 642108. The authors would like to thank Ingeteam Power Technology S.A. UP Service, part of the AWESOME Project Consortium providing the wind turbine data. ; Artigao, E.; Sapena-Bano, A.; Honrubia-Escribano, A.; Martinez-Roman, J.; Puche-Panadero, R.; Gómez-Lázaro, E. (2019). Long-Term Operational Data Analysis of an In-Service Wind ...

109 113 86 5 ; S ; [EN] Fault analysis of induction motors with broken bars or inter-turn short circuits needs accurate machine models to correctly identify and quantify the magnitude of the fault. Winding inductances and their derivatives are a key component of these models. In this paper a new, very easy and extremely fast method to compute them, based on the Magnetic Vector Potential (MVP), the Discrete Circular Convolution and the Fast Fourier Transform (FFT), is presented. This work was supported by the European Community's Seventh Framework Program FP7/2007-2013 under Grant Agreement 224233 (Research Project PRODI "Power Plant Robustification based on Fault Detection and Isolation Algorithms") Pineda-Sánchez, M.; Roger-Folch, J.; Pérez-Cruz, J.; Riera-Guasp, M.; Puche-Panadero, R.; Antonino-Daviu, J.; Pons Llinares, J. (2010). Calculation of Winding Inductances via Magnetic Vector Potential, Discrete Convolution and Fast Fourier Transform. Przegląd Elektrotechniczny. 86(5):109-113. http://hdl.handle.net/10251/103509 ; [Otro] Przedstawiono analiz¿ uszkodze¿ silnika indukcyjnego spowodowanych z¿amaniem pr¿tu, lub zwarciem wewn¿trznym. Oszacowano amplitud¿ wynikaj¿c¿ z uszkodzenia. Induktancja uzwoje¿ jest kluczowa w tym modelu. Zaproponowana metoda jest bardzo prosta i szybka. Zastosowano wektorowy potencja¿ magnetyczny oraz szybk¿ transformat¿ Fouriera.