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

• Autorzy: Firoozi H. , Bigdeli M.
• 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.

• Department of Electrical Engineering, Zanjan Branch Islamic Azad University, Zanjan, Iran,

Bibliografia

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