401 research outputs found

    Modeling and Lyapunov-designed based on adaptive gain sliding mode control for wind turbines

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    In this paper, modeling and the Lyapunov-designed control approach are studied for the Wind Energy Conversion Systems (WECS). The objective of this study is to ensure the maximum energy production of a WECS while reducing the mechanical stress on the shafts (turbine and generator). Furthermore, the proposed control strategy aims to optimize the wind energy captured by the wind turbine operating under rating wind speed, using an Adaptive Gain Sliding Mode Control (AG-SMC). The adaptation for the sliding gain and the torque estimation are carried out using the sliding surface as an improved solution that handles the conventional sliding mode control. Furthermore, the resultant WECS control policy is relatively simple, meaning the online computational cost and time are considerably reduced. Time-domain simulation studies are performed to discuss the effectiveness of the proposed control strateg

    Sveobuhvatan pregled LVRT mogućnosti i kliznog režima upravljanja vjetroagregata spojenog na mrežu s dvostruko napajanim asinkronim generatorom

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    In this paper, a comprehensive review of several strategies applied to improve the Low Voltage Ride-Through (LVRT) capability is presented for grid-connected wind-turbine-driven Doubly Fed Induction Generator (DFIG). Usually, the most proposed LVRT solutions in the literature based on: hardware solutions, which increase the system costs and software solutions, which increase the control system complexity. Therefore, the main objective of this study is to take into account grid requirements over LVRT performance under grid fault conditions using software solution based on Higher Order-Sliding Mode Control (HOSMC). Effectively, this control strategy is proposed to overcome the chattering problem and the injected stator current harmonics into the grid of the classical First Order Sliding Mode (FOSMC). Furthermore, the resultant HOSMC methodology is relatively simple; where, the online computational cost and time are considerably reduced. The LVRT capacity and effectiveness of the proposed control method, compared to the conventional FOSMC, are validated by time-domain simulation studies under Matlab on a 1.5 MW wind-turbine-driven DFIG.U ovom radu, prikazan je sveobuhvatan pregled strategija primjenjenih za poboljšanje sposobnosti rada tijekom prolaznih smetnji niskog napona mreže za vjetroagregat s dvostruko napajanim asinkronim generatorom (DFIG). Uobičajeno, većina predloženih LVRT rješenja u literaturi temelji se na: hardverskim rješenjima, što povećava troškove sustava i softverskih rješenja te složenost sustava upravljanja. Stoga je glavni cilj ovog istraživanja da se uključuje i zahtjevi mreže kroz ponašanje LVRTa u uvjetima mrežnih kvarova korištenjem softverskog rješenja zasnovanoga na kliznom režimu rada višeg reda (HOSMC). Efektivno, ova upravljačka strategija je predložena kako bi se prevladali oscilacije i ubacivanje harmonika struje statora u mrežu klasičnim metodama kliznog režima rada prvog reda (FOSMC). Nadalje, rezultantna metodologija HOSMC je relativno jednostavna; gdje su online računski zahtjevi i potrebno vrijeme značajno smanjeni. LVRT kapacitet i učinkovitost predložene metode upravljanja, u usporedbi s konvencionalnim FOSMC potvrđene su simulacijama u vremenskoj domeni u Matlabu na 1.5 MW vjetroagregatu s DFIG-om

    Ver-sur-Mer – British Normandy Memorial

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    Le projet de création d’un mémorial d’une surface de près de 18 ha à Ver-sur-Mer, au lieu-dit « Les Loges », a impliqué la prescription d’un diagnostic 7,8 ha correspondant à la surface réellement impactée. Les tranchées ont été ouvertes en fonction de la géographie du terrain, de l’axe des pentes mais également en fonction de la contrainte liée à l’environnement. Une opération de diagnostic contiguë, à l’ouest des parcelles AV 84 et 94, réalisée par une équipe du Service archéologie du Dépar..

    Deep-Learning and Vibration-Based System for Wear Size Estimation of Railway Switches and Crossings

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    The switch and crossing (S&C) is one of the most important parts of the railway infrastructure network due to its significant influence on traffic delays and maintenance costs. Two central questions were investigated in this paper: (I) the first question is related to the feasibility of exploring the vibration data for wear size estimation of railway S&C and (II) the second one is how to take advantage of the Artificial Intelligence (AI)-based framework to design an effective early-warning system at early stage of S&C wear development. The aim of the study was to predict the amount of wear in the entire S&C, using medium-range accelerometer sensors. Vibration data were collected, processed, and used for developing accurate data-driven models. Within this study, AI-based methods and signal-processing techniques were applied and tested in a full-scale S&C test rig at Lulea University of Technology to investigate the effectiveness of the proposed method. A real-scale railway wagon bogie was used to study different relevant types of wear on the switchblades, support rail, middle rail, and crossing part. All the sensors were housed inside the point machine as an optimal location for protection of the data acquisition system from harsh weather conditions such as ice and snow and from the ballast. The vibration data resulting from the measurements were used to feed two different deep-learning architectures, to make it possible to achieve an acceptable correlation between the measured vibration data and the actual amount of wear. The first model is based on the ResNet architecture where the input data are converted to spectrograms. The second model was based on a long short-term memory (LSTM) architecture. The proposed model was tested in terms of its accuracy in wear severity classification. The results show that this machine learning method accurately estimates the amount of wear in different locations in the S&C

    Chemical Modification of Xylan

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    Our study is part of the general context of valuing by-products from the wood industry, which consists of the chemical modification of xylan by synthesis of branched copolymers such as xylan-g-PLLA. The used xylan is extracted from chestnut and 4-dimethylaminopyridine (DMAP) is the catalyst. In fact, the synthesis of xylan-graft-poly (L-lactide) copolymer starting from natural and renewable resource products xylan and L-lactide is performed under different conditions. The results of the grafting reaction are unfavorable due to longer time because of depolymerization reactions. Another result is the solubility and insolubility of the copolymers synthesized in water. This first result indicates that there is a change in the properties of xylan. Moreover, the solubility of the xylan-g-PLLA copolymers is different from one study to another. Grafting of PLLA onto xylan was confirmed by Fourier transform infrared (FT-IR) and 1HNMR analyzes. The dynamic mechanical analysis showed that the xylan-g-PLLA plastic materials have interesting thermomechanical properties
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