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A Fuzzy Diagnostic System for Incipient Transformer Faults Based on DGA of the Insulating Transformer Oils

Ibrahim B. M. Taha(1), Sherif S. M. Ghoneim(2*), Hatim G. Zaini(3)

(1) Electrical engineering department, Taif University, Egypt
(2) Electrical engineering department, Taif University, Egypt
(3) Electrical engineering department, Taif University, Saudi Arabia
(*) Corresponding author


DOI: https://doi.org/10.15866/iree.v11i3.8453

Abstract


Some costly repairs are recited when faults occur in transformer, therefore,  an early detection of the transformer faults results in a reduction of the transformer maintenance and it maintains the continuous operation of the power networks. Nowadays, Dissolved Gas Analysis (DGA) is the most common diagnostic tool to determine the faults occurred in insulating transformer oils by analyzing the gas evolved from it. In this paper, the Fuzzy Logic Transformer Fault Diagnostic System (FLTFDS) is used as an application of the dissolved gas analysis to diagnose the dominant transformer fault generated  by  the electrical and thermal stresses. FLTFDS is constructed on the basis of three common criteria:the International Electro-technical Commission standard (IEC Code Standard), the Central Electric Generating Board (CEGB) Standard based on Rogers four ratios, and Finally Duval Triangle Method; these criteria are used to interpret the transformer faults using fuzzy logic. There are three main transformer diagnostic faults: thermal, arcing and partial discharge faults. The FLTFDS output is a dominant fault based on the output of the three criteria. The FLTFDS solves the conflict among the outputs of the three common criteria because such criteria, give different results for the same case study. Data samples (386 samples) are collected from the electrical utility laboratory in Egypt and credited literature. These data samples are used as an input to the three criteria and the outputs of the three criteria are an input to the Fuzzy-based decision making system (FDMS)in order to determine the dominant fault. The results demonstrate that the accuracy of FLTFDS output is greater than the accuracy of the three common criteria.
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Keywords


Fuzzy Logic System; Faults; Transformers; DGA

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References


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