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
The paper, prepared by CIGRE WG D1.03 (TF 09), presents the guidelines for risk assessment procedure on defects in GIS based on PD diagnostics. The procedure, described in detail in CIGRE Technical Brochure 525, starts with sensitive PD measurement to detect the critical defects and follows with identification of the type of the defect and its location inside the GIS. This information taken together with other essential data from laboratory measurements, manufacturer's experience, design aspects and trend analysis of the PD activity, are the base for the estimation of the criticality of the defects. Finally, the risk assessment is performed based on the estimated dielectric failure probability and failure consequences that can be different in case of on-site testing or in service activity.Index Terms -Gas insulated substation, defects, partial discharge measurements, diagnostics and risk assessment.
( Small defects in SF gas-insulated substations like fixed particles fixed to conduc-6 ) tors or on spacer surfaces or free moving particles can influence the insulation strength of the insulation system. To determine the risk of such defects on the insulation strength, identification of the PD source is one of the most important steps. In this paper, a method to identify defects based on statistical analysis of frequency spectra is introduced. Finally two examples of risk analysis of defects in GIS are shown.
Abstract-This paper introduces a new advanced partial discharge detection system for detecting partial discharge activity in the accessories of power cables during the acceptance test. The system consists of three autonomous PD measuring systems which communicate via a wireless communication network with one main computer. As a result, the measured data of each measuring unit can be displayed and analyzed at one single point near e.g. the voltage source which makes easy communication between the measuring technician and test engineer possible.Based on several field measurements performed in Europe on different 380kV and 150kV cables systems aspects of measurement and data processing are discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.