Abstract

This paper proposes a wavelet-based technique for monitoring nonstationary variations in order to distinguish between transformer inrush currents and transformer internal faults. The proposed technique utilizes a small set of coefficients of the local maxima that represent most of the signal's energy: only one coefficient at each resolution level is utilized to measure the magnitude of the variation in the signal. The data is processed while sliding through a Kaiser window and the technique has been applied in the laboratory as well as with simulated data, producing excellent results.

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