Identification of Transformer Oil incipient Faults Based on the Integration between Different DGA Techniques
نویسندگان
چکیده
منابع مشابه
Power Transformer Incipient Faults Monitoring
Power transformers are important and expensive components in the electric power system. The knowledge of the actual status of the transformer insulation behavior, load tap changer performance, temperature, and load condition is necessary in order to evaluate the service performance concerning reliability, availability and safety. Systems abnormalities, loading, switching and ambient condition n...
متن کاملPower Transformer Incipient Faults Diagnosis Based on Dissolved Gas Analysis
Incipient fault diagnosis of a power transformer is greatly influenced by the condition assessment of its insulation system oil and/or paper insulation. Dissolved gas-in-oil analysis (DGA) is one of the most powerfull techniques for the detection of incipient fault condition within oil-immersed transformers. The transformer data has been analyzed using key gases, Doernenburg, Roger, IEC and Duv...
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15 صفحه اولA New Approach for Transformer Incipient Fault Diagnosis Based on Dissolved Gas Analysis (DGA)
Transformer incipient fault diagnostic method based on dissolved gas analysis (DGA) using Artificial Neural Networks (ANN) and Neural-Imperialistic Competitive Algorithm (Nero-ICA) hybrid approach is simulated in this paper and the results has been compared with IEC standard. Firstly, dissolved gas analysis method and IEC DGA standard has been presented. In the second step, application of ANN a...
متن کاملDGA Interpretation of Oil Filled Transformer Condition Diagnosis
Copyright 2012 KIEEME. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited. pISSN: 1229-7607 eISSN: 2092-7592 DOI: http://dx...
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ژورنال
عنوان ژورنال: Delta University Scientific Journal
سال: 2023
ISSN: ['2636-3054', '2636-3046']
DOI: https://doi.org/10.21608/dusj.2023.291093