A classification procedure for the automatic separation of pulse-signals generated by multiple sources simultaneously active during Partial Discharge (PD) measurements, is presented in this paper. It is based on the analysis of signals projected into a 3D space obtained selecting three different components where the maximum dispersion of the Normalized Auto-Correlation Function (NACF), is found. Assuming that the same source can exhibit NACFs having similar shapes, those which show different shapes are grouped differently in this space. The DBSCAN algorithm modified to take into account clusters partially overlapped, is adopted here to separate the different groups. The relevant phase resolved PD subpatterns are derived accordingly. Improvements with respect to the current separation methods are also discussed.
Automatic Separation of Multiple PD Sources Using an Amplitude-Autocorrelation Relation Diagram
CONTIN, ALFREDO;PASTORE, STEFANO
2012-01-01
Abstract
A classification procedure for the automatic separation of pulse-signals generated by multiple sources simultaneously active during Partial Discharge (PD) measurements, is presented in this paper. It is based on the analysis of signals projected into a 3D space obtained selecting three different components where the maximum dispersion of the Normalized Auto-Correlation Function (NACF), is found. Assuming that the same source can exhibit NACFs having similar shapes, those which show different shapes are grouped differently in this space. The DBSCAN algorithm modified to take into account clusters partially overlapped, is adopted here to separate the different groups. The relevant phase resolved PD subpatterns are derived accordingly. Improvements with respect to the current separation methods are also discussed.Pubblicazioni consigliate
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