PD measurement is a worldwide-accepted method for insulation diagnosis and a required part of the acceptance testing for many HV assets. To facilitate PD measurements different techniques/methods have been developed and they are in use for laboratory and on-site applications. All these methods can be divided into conventional and unconventional PD measuring methods. The latter are the subject of this guide.@en

Different diagnostic techniques are currently available for on-line insulation condition assessment of power transformers. Amongst these techniques a relatively new technique for detecting partial discharges (PD) in the Ultra High Frequency range of the spectrum is also introduced. The UHF technique has been recently presented in the field of transformer diagnostics, and although it is under development it shows great potential for on-line detection, recognition and location of PD activity. This paper describes the practical application of the UHF technique on two new identical 90 MVA, 150 kV power transformers. Both transformers are equipped with four external UHF sensors. Initially, injection measurements were performed to investigate the effects experienced by UHF signals when propagating through the transformer. Moreover, software developed to model the propagation of UHF signals inside the transformer tank was tested in its application to these specific transformers. The results obtained during the both the induced voltage test, as well as during the PD acceptance test in the factory are described. The practical experiences related in this paper provide further insight into the application of UHF PD monitoring techniques to power transformers.@en

The abstraction of meaningful diagnostic information from raw condition monitoring data in domains where diagnostic expertise and knowledge is limited and constantly evolving presents a significant research challenge. Expert diagnosis and location of partial discharges in high voltage electrical plant is one such domain. This paper describes the functionality of a knowledge-based decision support system capable of providing engineers with a comprehensive diagnosis of the defects responsible for partial discharge activity detected in oil-filled power transformers. Plant data captured from partial discharge (PD) sensors can be processed to generate phase-resolved partial discharge (PRPD) patterns. This paper proposes a means of abstracting the salient features characterizing the observed PRPD patterns. Captured knowledge describing the visual interpretation of these patterns can be applied for defect diagnosis and location. The knowledge-based PRPD pattern interpretation system can support on-line plant condition assessment and defect diagnosis by presenting a comprehensive diagnosis of PD activity detected and classification of the defect source. The paper also discusses how the system justifies its diagnosis of the PD activity to offer the expert greater confidence in the result, a feature generally absent in 'black-box' pattern recognition techniques. The incremental approach exhibited by the system reflects that of a PD expert's visual interpretation of the PRPD pattern. The paper describes how this functional system design has evolved from the approach taken by PD experts to the visual interpretation of PRPD patterns.@en