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A new technique for partial discharge (PD) source location in cable systems is presented in this paper. Such technique, here referred to as amplitude-frequency (AF) mapping, is based on the influence of attenuation and dispersion phenomena on PD pulse time and frequency characteristics. A comparative evaluation with other two well-known location techniques, i.e., time-domain reflectometry (TDR) and arrival time analysis (ATA) is presented through working cases. The results indicate that while TDR is appropriate for short cable systems, for longer cable systems, location by AF mapping can be obtained directly from PD testing, without additional efforts. The location thus achieved is, in most cases, accurate enough to allow maintenance practices to be carried out effectively. In some cases, ATA can be necessary to refine location and resolve ambiguities. Index Terms--Partial discharges, power cables, time domain reflectometry, fault location.

Inter-time (i.e., the time that separates a PD event from the next one) distribution analysis has been recently proposed as a tool to infer the presence of trees in solid insulation systems. In this paper, inter-time distribution analysis is improved to infer more accurately trees at an early growth stage. Measurements from both artificial specimens as well as practical objects are presented to support the effectiveness of this tool. Moreover, considerations on inter-time analysis robustness with respect to both noise interference and other partial discharge sources are reported. Index Terms--Electrical trees, partial discharges, fuzzy logic.

Applications of a new methodology, aimed at the identification of defects occurring in insulation systems of HV apparatus and based on partial discharge (PD) measurements, are presented in this paper. This methodology relies upon the digital acquisition of a large amount of PD pulses and separates the acquired pulses into homogeneous sub-classes. Signal processing tools recognize the presence of noise among the different classes. Identification of basic PD source typologies (i.e., internal, corona and surface discharges) is then achieved, resorting to fuzzy algorithms. The proposed procedure is applied to measurements performed on different HV apparatus, such as cables, transformers and rotating machines. The purpose of this paper is to show that the identification process is robust, regarding the measuring circuit, and flexible, so that it can constitute an advanced tool for condition based maintenance, guiding maintenance experts in making decisions on the condition of the insulation system under test. Index Terms--Partial discharges, solid insulation systems, diagnostics, condition based maintenance.

Noise rejection, defect identification and degradation diagnosis in on-field partial discharge measurements are sought by industry, but hardly achieved in practice. This paper presents tools for automatic noise suppression in measurements performed by ultra wide band digitizers, able to record a large quantity of partial discharge (PD) pulse waveforms. Noise and PD signals are split in different classes on the basis of their shape by means of a fuzzy classifier. Tools used for establishing whether a given class of recorded signals is due to external noise or not are proposed. As an example, two kinds of noise are considered: random noise and rectifier-generated noise. A companion paper will explain how the same classification tools can be employed for the purpose of defect identification. Index Terms--Partial discharges, noise measurement, noise suppression, random noise, rectifier-generated noise, cross talk, identification.

This paper deals with digital acquisition, classification and analysis of the stochastic features of random pulse signals generated by partial discharge (PD) phenomena. Focus is made on a new measuring system for the digital acquisition of PD-pulse signals, which operates at a sampling rate high enough to avoid the frequency aliasing, but that provides an amount of PD pulses which enables PD stochastic analysis. A separation and classification method, based on a fuzzy classifier, is developed for the analysis of the acquired PD-pulse shape signals. The result of the fuzzy classification is a cluster of signals homogeneous in terms of stochastic features of PD pulses. The classification efficiency is evaluated resorting to the PD-pulse height and phase distributions analysis. The instrumentation, and the associated classification methodology, are applied to measure and analyze PD data recorded for mica-insulated stator bars and coils, where typical defects, occurring during normal operations, were simulated. It is shown that the proposed procedure enables PD-source identification to solve the identification problems which arise, in particular, when different sources of PD are simultaneously active. In addition fuzzy classification provides an efficient noise-rejection tool.

The article discusses the measurement and analysis of partial discharges (PD) as the main and the most effective tool in discovering local damage and flaws in cable systems. The methods of separation which is based on the deterioration of pulse frequency and identification resulted in improved reliability of PD assessment. Therefore, it offers information that can be used to develop maintenance procedure plans which is key in cutting operational costs in utility cable network.

Discusses an emerging approach which can be used to diagnose solid insulation systems based on partial discharge signal interference. Detection of partial discharge-pulse signals; Problem related to signal separation; Purpose of the noise recognition stage; Identification of basic defect characteristics.