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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-article-BPS4-0005-0032

Czasopismo

Archives of Electrical Engineering

Tytuł artykułu

A new method for evaluation of transformer drying process using transfer function analysis and artificial neural network

Autorzy Firoozi, H.  Bigdeli, M. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Since a few years ago, there is an increasing interest for utilization of transfer functions (TF) as a reliable method for diagnosing of mechanical faults in transformer structure. However, this paper aims to develop the application of TF method in order to evaluate the drying quality of active part during the manufacturing process of transformer. To reach this goal, the required measurements are carried out on 50 MVA 132 KV/33 KV power transformer when active part is placed in the drying chamber. Two different features extracted from the measured TFs are then used as the inputs to artificial neural network (ANN) to give an estimate for required time in drying process. Results show that this new represented method could well forecast the required time. The results obtained from this method are valid for all the transformers which have the same design.
Słowa kluczowe
EN transformer   drying process   transfer function   artificial neural network  
Wydawca Polish Academy of Sciences, Committee on Electrical Engineering
Czasopismo Archives of Electrical Engineering
Rocznik 2013
Tom Vol. 62, nr 1
Strony 153--162
Opis fizyczny Bibliogr. 16 poz., rys.
Twórcy
autor Firoozi, H.
autor Bigdeli, M.
Bibliografia
[1] Firoozi H., Karami S., Experimental attempts and field experiences to fault diagnosis of power transformersusing FRA technique. International Review of Electrical Engineering (IREE) 6: 2221-2228 (2011).
[2] Leibfried T., Feser K., Monitoring of power transformers using the transfer function method. IEEE Transaction on Power Delivery 14: 1333-1341 (1999).
[3] Rahimpour E., Jabbari M., Tenbohlen S., Mathematical comparison methods to assess transferfunctions of transformers to detect different types of mechanical faults. IEEE Transaction on Power Delivery 25: 2544-2555 (2010).
[4] Bigdeli M., Vakilian M., Rahimpour E., A new method for detection and evaluation of windingmechanical faults in transformer through transfer function measurements. Advances in Electrical and Computer Engineering 11: 23-30 (2011).
[5] Bigdeli M., Vakilian M., Rahimpour E., Transformer winding faults classification based on transferfunction analysis by support vector machine. IET Electric Power Applications 6: 268-276 (2012).
[6] Bigdeli M., Vakilian M., Rahimpour E., Comparison of Transfer Functions Using Estimated RationalFunctions to Detect Winding Mechanical Faults in Transformers. Archives of Electrical Engineering 61: 85-99 (2012).
[7] Rahimpour E., Tenbohlen S., Experimental and theoretical investigation of disc space variation inreal high-voltage windings using transfer function method. IET Electric Power Applications 4: 451-461 (2010).
[8] Ryder S., Diagnosing a wide range of transformer faults using frequency response analysis. Presented at the 13th Int. Symp. High Voltage Engineering (2003).
[9] Wang M., Vandermaar A.J., Srivastava K.D., Improved detection of power transformer windingmovement by extending the FRA high frequency range. IEEE Transaction on Power Delivery 20: 1930-1938 (2005).
[10] Akbari A., Firoozi H., Kharezi M., Investigations on sensitivity of frequency response analysis techniqueto measuring setup. Presented at the 15th Int. Symp. High Voltage Engineering (2007).
[11] Akbari A., Firoozi H., Borsi H., Kharezi M., Assesment of Drying Quality for Power TransformersDuring Manufacturing Process Using Variation of Transfer Function, IEEE/CEIDP 2006, 15-18, Kansas City, Missouri, USA (2006).
[12] Secue J.R., Mombello E., Sweep frequency response analysis (SFRA) for the assessment of windingdisplacements and deformation in power transformers. Electric Power Systems Research: 78: 1119-1128, (2008).
[13] Rahimpour E., Tenbohlen S., Fault diagnosis of actual large-power high-voltage windings usingtransfer function method. Archives of Electrical Engineering 60: 269-281 (2011).
[14] Ryder S.A., Diagnosing transformer faults using frequency response analysis. IEEE Electrical Insulation Magazine 19: 16-22 (2003).
[15] Haykin S., Neural networks - a comprehensive foundation, Macmillan college publishing company, New York, (1994).
[16] MATLAB Neural Network Toolbox, Version 5, MathWorks Inc (2006).
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