An Advanced Fuzzy Logic Based Method for Power Transformers Assessment

摘要

Dissolved Gas Analysis is an effective method for detecting faulty power transformers in their early stages. However, technical interpretation of results can be complex and highly dependent on the experience of experts. This paper presents an attempt to detect power transformer incipient fault via gas concentrations obtained from oil sampling and Dissolved Gas Analysis. The proposed method uses a sophisticated fuzzy logic system to perform fault type classification. Ratios and relative percentages of 5 key gases (Hydrogen, Methane, Ethane, Ethylene, and Acetylene) are taken as input variables, then the fuzzy system will try to generate an output vector that indicates six basic fault types, including partial, low, and high energy discharges as well as three ranges of thermal fault. This method can be easily implemented in any environment that supports basic mathematical operators. To demonstrate how the proposed fuzzy logic method works, the authors developed an offline MATLAB script and an online web-based application that can provide multiple assessments by various methods simultaneously. The set of membership functions and fuzzy rules presented in this paper allows the detection of multiple faults at once. Performance tests on many actual data sets show that the proposed method achieves better accuracy than the traditional ratio codes, even on a par with state-of-the-art graphical-based tools such as the Duval triangle or pentagon.