Recovery of Partial Discharge Signal and Noise Cancellation in Power Transformer Using Radial Basis Function

The presence of noise causes disturbance in the signal received by the sensor which is installed on the transformer. A nonlinear signal processing is required to effectively extract the signal. In this article, the radial basis function network (RBFN) was used to extract and eliminate the unwanted s...

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Bibliographic Details
Published in:	IEEE transactions on instrumentation and measurement Vol. 69; no. 6; pp. 3388 - 3394
Main Authors:	Khavari, Ehsan, Hassan Hosseini, Seyed Mohammad, Gharehpetian, G. B.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01-06-2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	CST software Discharge Frequency-domain analysis Interference Noise noise cancellation Nondestructive testing nonlinear mapping partial discharge Partial discharges power transformer Power transformer insulation Radial basis function radial basis function (RBF) Radial basis function networks Signal processing Transformers Wavelet transforms
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Summary:	The presence of noise causes disturbance in the signal received by the sensor which is installed on the transformer. A nonlinear signal processing is required to effectively extract the signal. In this article, the radial basis function network (RBFN) was used to extract and eliminate the unwanted signal in case of the presence of a partial discharge source in the transformer. Elimination of the signal is due to the potential of the RBFN to approximate the nonlinear functions. The transformer, partial discharge, and noise sources are simulated in the CST software environment. Studies showed that the RBFN can successfully extract the unwanted source when it is integrated with the partial discharge signal.
ISSN:	0018-9456 1557-9662
DOI:	10.1109/TIM.2019.2938054