Narzędzia help

Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
first last
cannonical link button

http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-article-BPOK-0038-0056

Czasopismo

Przegląd Elektrotechniczny

Tytuł artykułu

Speed Estimation of Brushless Direct Current (BLDC) Motor with Multilayer Perceptron

Autorzy Serteller N.F.  Bektas, Y.  Nogay, S.  Akinci, T.C. 
Treść / Zawartość http://pe.org.pl/
Warianty tytułu
PL Określanie prędkości obrotowej silnika BLDC przy wykorzystaniu wielowarstwowego perceptronu
Języki publikacji EN
Abstrakty
EN This study used an artificial neural network model to estimate the revolutions per minute of a brushless direct current (BLDC) motor operating at different driver modes and different load currents. The dataset that was used to train and test the artificial neural network model was obtained from experimental applications and was made applicable for the training of a multilayer perceptron. A total of 7643 data items were used in the study. Of these data, 382 were used to test the ANN model. Test results indicated that the multilayer perceptron provided 99.34% estimation and that the target and the results were quite close.
PL W artykule zaprezentowano wykorzystanie sieci neuronowej do określania prędkości obrotowej bezszczotkowgo silnika BLDC pracującego przy różnych prądach obciążenia. Do trenowania sieci użyto danych eksperymentalnych.
Słowa kluczowe
PL sieć neuronowa   silnik BLDC  
EN multilayer perceptron   brushless direct current motor  
Wydawca Wydawnictwo SIGMA-NOT
Czasopismo Przegląd Elektrotechniczny
Rocznik 2012
Tom R. 88, nr 9a
Strony 255--260
Opis fizyczny Bibliogr. 22 poz., rys., wykr.
Twórcy
autor Serteller N.F.
autor Bektas, Y.
autor Nogay, S.
autor Akinci, T.C.
Bibliografia
[1] Juan W. Dixon, Ivan Leal; Current control strategy for brushless dc motors based on a common dc signal. IEEE Transactions on Power Electronics, 17(2), March (2002).
[2] K.S. Low M.F. Rahman and K.W. Lim. Approaches to the control of torque and current in a brushless dc drive. March- April (2005).
[3] Texas Instruments Incorporated. DSP Solutions for BLDC Motors, (1997).
[4] Yurtoglu H.,Yapay Sinir Ağları Metodolojisi ile Öngörü Modellemesi: Bazı Makroekonomik Degişkenler İçin Türkiye Örneği. February, T.C. DPT, (2005).
[5] Alexander, I. ve Morton, H.; An Introduction to Neural Computing, London: Chapman and Hall, 1990.
[6] Anderson, D. ve McNeil, G.; Artificial Neural Networks Technology, Data & Analysis Center for Software, Kaman Sciences Corparation, (1992), Newyork, USA.
[7] Aydogmus Z., A neural network-based estimation of electric fields along high voltage insulators. Expert Systems with Applications (2009), 36,8705–8710.
[8] Hagan T.M., Demuth HB, Beale M., Neural Network Design. PWS Publishing Company, Boston, 1996,pp.2-44.
[9] Bose B.K.; Modern Power Electronics and Ac Drives, Prentice Hall PTR, USA, (2002), 625-689.
[10] Nogay, H.S., Prediction of Internal Temperature in Stator Winding of Three-Phase Induction Motors with ANN, European Transactions on Electrical Power, 20:1–9. DOI: 10.1002. 2010.
[11] Akcayol, M.A., Cetin A, Elmas, C,; An educational tool for fuzzy logic-controlled BDCM, (2002), 45, 33-42.
[12] Gotou, M., Ochi, M., A new drive system of a brushless motor reducing power consumption and motor vibration simultaneously, IEEE International Conference on power electronics and drive systems, PEDS'99, July (1999), Hong Kong.
[13] Sway C.L.P., Singh, B., Singh, B.P., Murty, S.S.; Experimental investigations on a Permanent Magnet Brushless DC motor fed by a PV array for a water pumping system, Journal of solar energy, (2000), 122, 129-130.
[14] Karady, G.G., Increasing student interest and comprension in power engineering education at the graduate and undergraduate level, (2000), 1, 12-21.
[15] Park, S.J., Park H.W., Lee M.H.; Harashima, F, A new approach for minimum torque ripple maximum efficiency control of BLDC, (2000), 47, 109-114.
[16] Bolton HR, Ashen RA, Influence of motor design and feedcurrent wave form on torque ripple in brushless DC drive Proc. Ins. Elec. Eng. 1984,131, pp.82-90.
[17] Haskew, T.A, Schinstock D.E, Bredeson J.G., Salem E.T.; Brushless machine monitoring and simulation Proceedings of the Intersociety, Energy Conversion Engineering Conference,Washington DC USA, Agust 11-16, (1996).
[18] Haskew, T.A., Jackson, D.J.; Real-time simulation methods for a six-pulse converter Electric Power Systems Research, (1995),33, 69-75.
[19] Bodner, G.M., Why good teaching fails and hard working students do not always succeed. Spec (1990), 28, 27-32.
[20] Jang, G, Kim, MG,; A bipolar starting and unipolar running method to drive a hard disk drive spindle motor at high speed with large starting torque 2005,41, pp.750-755.
[21] Zhong, M.P., Zheng, S.Y. Pan, X.H.;Design of direct-drive air compressor drived by permanent magnet brushless DC motor Engineering Science, (2009), 43, 495-499.
[22] Akinci, T.C., Nogay, H.S.,Gokmen,G., Determination of Optimum Operation Cases in Electric Arc Welding Machine, Using Neural Network, Journal of Mechanical Science and Technology, (2011),25 (4), 1253-1260.
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-article-BPOK-0038-0056
Identyfikatory