Journal
MEASUREMENT SCIENCE AND TECHNOLOGY
Volume 28, Issue 1, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1361-6501/28/1/015005
Keywords
vibration; power transformer; nonlinear system identification; Fourier neural networks
Funding
- Science and Technology Project of the Zhejiang Electric Power Company of the State Grid of China [ZB13-026B-039]
- China National Science Foundation [11574269, 11504324, 61603335]
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This paper focuses on the identification of the nonlinear vibration system of power transformers. A Hammerstein model is used to identify the system with electrical inputs and the vibration of the transformer tank as the output. The nonlinear property of the system is modelled using a Fourier neural network consisting of a nonlinear element and a linear dynamic block. The order and weights of the network are determined based on the Lipschitz criterion and the back-propagation algorithm. This system identification method is tested on several power transformers. Promising results for predicting the transformer vibration and extracting system parameters are presented and discussed.
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