The Application of Fuzzy System Group in Intelligent Diagnosis for Power Tranformer

For a long time, the fault diagnosis and assessment for power transformer is a quite complex and difficult problem. In this paper, we propose a transformer fault diagnosis method based on fuzzy theory. The dissolved gas concentrations are set as the inputs of the system, and a fuzzy system group is...

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Bibliographic Details
Published in2011 Second International Conference on Digital Manufacturing & Automation pp. 1206 - 1209
Main Authors Deyin Ma, Yanchun Liang, Xiaoshe Zhao, Zhexue Li, Xiaohu Shi
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2011
Subjects
Artificial intelligence
Discharges
Dissolved Gas Analysis
Fault diagnosis
Fuzzy system
Fuzzy system group
Fuzzy systems
Oil insulation
Power transformer insulation
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Summary:For a long time, the fault diagnosis and assessment for power transformer is a quite complex and difficult problem. In this paper, we propose a transformer fault diagnosis method based on fuzzy theory. The dissolved gas concentrations are set as the inputs of the system, and a fuzzy system group is appLied to build the intelLigent diagnosis system. The parameters of the system, including the input dimension, output dimension, and the membership functions, can be set up in whole or separately in the system. To test the effectiveness of the proposed method, it is appLied to the practice dataset. The experiment results show that the fuzzy system group improves the accuracy of assessment greatly compared with fuzzy system and BP neural networks. Also, the knowledge system of power transformer fault diagnosis can be built up completely by the proposed method.
ISBN:1457707551
9781457707551
DOI:10.1109/ICDMA.2011.297