A Fuzzy-Based Fault Diagnostic Model for Oil-Immersed Load Tap Changers

Failures of oil-immersed load tap changer (LTC) is majorly occurred due to its deteriorated insulation. This will consequently cause the entire transformer unit to be damaged. In general, an early warning of LTC breakdown is provided by interpreting the dissolved gases using the most recent Duval triangle 2. In the present paper, a novel fuzzy logic model representing the conventional Duval triangle 2 is proposed to identify the incipient faults present in oil-immersed LTCs. It incorporates all the possible conditions of conventional Duval triangle method. Various faults present in LTCs are identified using percentages of dissolved gases. The fault outputs obtained from the proposed fuzzy logic model are compared with the conventional Duval triangle method incorporated in Reference (Duval in IEEE Electr Insul Mag 24:22–29, 2008 [1]). It has been observed that the conventional method requires a special algorithm based technology for identifying the faults. Moreover, it has uncertainty in overlapping of multiple number of faults in Duval triangle 2. The proposed fuzzy logic model is designed to identify LTC faults in form of numerical indices, and hence overcome the above discussed limitations. The proposed fuzzy logic model is very simple in implementation, and easily handled by any expert or utility managers of transformers.