標題: Fuzzy approaches for fault diagnosis of transformers
作者: Chen, AP
Lin, CC
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: cluster analysis;linguistic modeling;approximate reasoning;transformer diagnosis;dissolved gas analysis
公開日期: 16-Feb-2001
摘要: Dissolved gas analysis has been used as a diagnostic method to determine the conditions of transformers for a long time. The criteria used in dissolved gas analysis are based on crisp value norms. Due to the dichotomous nature of crisp criteria, transformers with similar gas-in-oil conditions may lead to very different conclusions of diagnosis especially when the gas concentrations are around the crisp norms. To deal with this problem, gas-in-oil data of failed transformers were collected and treated in order to obtain the membership functions of fault patterns using a fuzzy clustering method. All crisp norms are fuzzified to linguistic variables and diagnostic rules are transformed into fuzzy rules. A fuzzy system originally proposed by Takagi and Sugeno is used to combine the rules and the fuzzy conditions of transformers to obtain the final diagnostic results. It is shown that the diagnosing results from the combination of several simple fuzzy approaches are much better than traditional methods especially for transformers which have gas-in-oil conditions around the crisp norms. (C) 2001 Elsevier Science B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/S0165-0114(99)00115-3
http://hdl.handle.net/11536/29837
ISSN: 0165-0114
DOI: 10.1016/S0165-0114(99)00115-3
期刊: FUZZY SETS AND SYSTEMS
Volume: 118
Issue: 1
起始頁: 139
結束頁: 151
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