Neutral current wave shape analysis using wavelet for diagnosis of winding insulation of a transformer

Insulation failure within the windings of a power transformer arises due to over voltages, under voltages, notches, glitches, etc. A widely used technique to detect these power transformer insulation failures during an impulse test is the comparison of neutral current waveforms. Any shift in the recorded waveforms between reduced and full voltage confirms the existence of a fault in the windings. Hence, a proper analysis of neutral current waveforms is necessary to assess the condition of the insulation of power transformer winding. In order to carry out a wave shape analysis, a 61 MVA, 11.5/230 kV generator transformer is used and faults are created in the disks of high-voltage windings at specific locations. Neutral currents are recorded by applying a 100 V, low-voltage impulse. Noise inherent in the neutral current during recordings is isolated using a biorthogonal wavelet and the denoised signals are analyzed using the Shannon wavelet for identification of a fault in the winding.

Neutral current wave shape analysis using wavelet for diagnosis of winding insulation of a transformer

Insulation failure within the windings of a power transformer arises due to over voltages, under voltages, notches, glitches, etc. A widely used technique to detect these power transformer insulation failures during an impulse test is the comparison of neutral current waveforms. Any shift in the recorded waveforms between reduced and full voltage confirms the existence of a fault in the windings. Hence, a proper analysis of neutral current waveforms is necessary to assess the condition of the insulation of power transformer winding. In order to carry out a wave shape analysis, a 61 MVA, 11.5/230 kV generator transformer is used and faults are created in the disks of high-voltage windings at specific locations. Neutral currents are recorded by applying a 100 V, low-voltage impulse. Noise inherent in the neutral current during recordings is isolated using a biorthogonal wavelet and the denoised signals are analyzed using the Shannon wavelet for identification of a fault in the winding.

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