Partial Discharge Location Through Application of Stationary Discrete Wavelet Transform on UHF Signals
The degradation level of high voltage equipment insulation systems can be estimated from the monitoring of partial discharge (PD) activity. The radiometric method stands out as one of the most promising methods for monitoring these discharges, however, in substations, the PD signals may be susceptib...
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Veröffentlicht in: | IEEE sensors journal 2021-11, Vol.21 (21), p.24644-24652 |
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Sprache: | eng |
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Zusammenfassung: | The degradation level of high voltage equipment insulation systems can be estimated from the monitoring of partial discharge (PD) activity. The radiometric method stands out as one of the most promising methods for monitoring these discharges, however, in substations, the PD signals may be susceptible to external interference and, in some cases, hide by background noise. This work presents the application of the stationary discrete wavelet transform (SDWT) over PD signals measured by bio-inspired printed monopole antennas (PMA) operating at the UHF frequency range (300-3000 MHz). In addition to the filtering from the SDWT, the use of the SDWT scaling coefficients energy is evaluated as a support tool for the location of PD. The PD signals are investigated under low signal-to-noise ratio (SNR) and; high SNR with a high pulse repetition rate. These signals are obtained from a laboratory setup composed by a discharge generating oil cell, and acquired through a bio-inspired PMA. After the application of the SDWT over the evaluated signals, together with the energy calculation using different mother wavelets, it is verified that the proposed methodology provides an efficient filtering result, being appropriate for PD detection. From the energy of SDWT scaling coefficients, it is possible to highlight the constant delays between the detection of consecutive pulses, minimally interfering over the time differences of arrival and providing better location results. |
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ISSN: | 1530-437X 1558-1748 |
DOI: | 10.1109/JSEN.2021.3116491 |