Multisource PD identification based on phase synchronous and asynchronous data

Abstract

Partial Discharge (PD) measurements in cables and their accessories play a fundamental role in Condition Based Monitoring (CBM) of High Voltage (HV) equipment. CBM monitoring has been enforced by utilities in the transmission and distribution (T&D) environment as part of a predictive maintenance program that aims to result in less unscheduled downtime and lower maintenance cost. Identifying the source of a PD rather than merely assessing its magnitude provides additional information that could enable more educated decisions concerning the integrity of the insulation to be made. In on-line scenarios the presence of multiple PD sources that are simultaneously active as well as the presence of interference, complicates the identification process. In this paper, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm has been employed to identify PDs of different sources. Phase synchronous measurements were acquired in the laboratory and pre-processed through a peak detection algorithm to extract the single pulses (phase asynchronous). To extract a feature the Wavelet Packet Transform (WPT) and Higher Order Statistics (HOS) were employed according to previous work by the authors. The feature was then analyzed by the Principal Component Analysis (PCA) for dimensionality reduction and study of different PD sources has been shown to form separate clusters. Application of this method on on-line data acquired from the network of the Electricity Authority of Cyprus (EAC) has demonstrated its potential use in PD identification and interference rejection.