An Effective Health Assessment of Transformers Using Multi-criterion-Based Triangular Fuzzy Logic Model

In the present work, we introduce a novel multi-criterion-based triangular fuzzy logic model to determine the overall health index (OHI) of the power transformer. This model handles the diagnostic data of various influencing attributes of oil and paper insulation. Those include total dissolved hydrocarbon gases, acidity, water content, 2-furfuraldehyde, etc. The data of fifteen transformer samples collected from state electricity board Himachal Pradesh were utilized for validating the proposed model. Initially multi-criterion analysis is used for normalizing the raw data into three attributes scores, i.e., total dissolved hydrocarbon gases, oil insulation, and paper insulation. The accuracy of proposed triangular fuzzy logic model is compared with trapezoidal fuzzy logic model proposed in (Ranga et al. in IET Sci Measure Technol 11(8), 983–990, 2017 [4]). It is proved that the model is on par in accuracy and simpler than trapezoidal fuzzy model. In addition, it is very easy to implement for utility managers in industrial transformer monitoring.