Diagnosis of incipient dominant and boundary faults using composite DGA method

Abstract

Summary In this paper, an effort is being made to develop a fault diagnosis algorithm using Duval triangle method of dissolved gas analysis (DGA) as a backbone for more reliable fault diagnosis. The algorithm is based on integrated model which is the fusion of Duval triangle and IEC ratio method. It uses the conventional Duval triangle rules to detect dominant faults and IEC method rules to detect “no” and boundary faults. Hence, the proposed method simultaneously checks the normal operating conditions, boundary and dominant fault cases. A graphical‐user interface (GUI) has also been prepared using LabVIEW. Study of fault severity is also carried out for various Duval triangle zones. Fault severity is determined using concept of energy weighing, and fuzzy model has been developed for the same. The system has been tested using a fault database and shows accuracy of 93.6%. Results presented indicate a trend towards a more reliable system.

Classification of Cellulosic Insulation State Based on Smart Life Prediction Approach (SLPA)

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Multiple incipient fault classification approach for enhancing the accuracy of dissolved gas analysis (DGA)

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Detecting the location and severity of transformer winding deformation by a novel adaptive particle swarm optimization algorithm

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