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    Standardization of DGA interpretation techniques using fuzzy logic approach

    189241_189241.pdf (667.0Kb)
    Access Status
    Open access
    Authors
    Hmood, S.
    Abu-Siada, Ahmed
    Masoum, Mohammad Sherkat
    Islam, Syed
    Date
    2012
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Hmood, S. and Abu-Siada, A. and Masoum, Mohammad A.S. and Islam, Syed M. 2012. Standardization of DGA interpretation techniques using fuzzy logic approach, in Proceedings of the 2012 International Conference on Condition Monitoring and Diagnosis, Sep 23-27 2012, pp. 929-932. Bali, Indonesia: IEEE.
    Source Title
    IEEE
    Source Conference
    International Conference on Condition Monitoring and Diagnosis
    DOI
    10.1109/CMD.2012.6416305
    Remarks

    Copyright © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    URI
    http://hdl.handle.net/20.500.11937/7332
    Collection
    • Curtin Research Publications
    Abstract

    Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results. However, all of these techniques rely on personnel experience more than standard mathematical formulation. As a result, various DGA interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. DGA interpretation is yet a challenge in the power transformer condition monitoring research area. To alleviate this issue, this paper introduces a fuzzy logic approach to help in standardizing DGA results quantification and classification using various interpretation techniques such as key gas, Rogers ratio, IEC ratio, Doernenburg and Duval triangle methods. In this context, DGA results for 2000 oil samples have been collected from different transformers of different ratings, life span and operating conditions. Traditional DGA interpretation techniques are used to analyze the results which are then compared with the results of the fuzzy logic models. Results show that the fuzzy logic models enhance the consistency among all current interpretation techniques and can eliminate the need for expert personal to interpret DGA results.

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