An algorithm, based on autocorrelation function evaluation, for the separation of partial discharge signals

An innovative classification method for the automatic separation of partial discharge signals, based on the auto and cross correlation function evaluation, is presented in this paper. Two different parameters, derived from the analysis of these two functions, are used to evaluate the similarity of signal shapes. Reasonable threshold levels have been established as a good compromise between strong and weak discrimination between pulses. Examples of application of the proposed algorithm to data from laboratory tests are reported and discussed to show the validity of the method.