Analyzing Chemical Degradation of Power Transformers Using Smart Intelligence System

Transformers are the critical components of any power transmission network and are vulnerable to failure for several reasons. The deterioration of the insulation materials used in a power transformer might fail. The prevailing environmental conditions, including temperature, moisture, and oxygen content, affect how quickly the insulation degrades. In this study, a fuzzy based approach is employed to compute the overall chemical degradation of the transformer using crisp input data from multiple diagnostic tests. Here, the chemical degradation of each transformer component is computed, and fuzzy sub-models are constructed using weighted fuzzy rules to increase the model's efficacy. Based on the calculated chemical criticality index, creative fuzzy models are created to compute automatically and suggest the most appropriate action to take.