Design of expert system for health index of distribution capacity regulating transformer based on intuitionistic fuzzy set theory

In this paper, an expert system for distribution capacity regulating transformer health index based on intuitionistic fuzzy set theory is designed to address the current problems in distribution capacity regulating transformer health assessment, such as the difficulty of systematic extraction and utilization of expert experience, the lack of intelligent reasoning mechanism in the diagnostic process, and the inability of knowledge to be self-updated. The system takes the comprehensive seminar hall as the core knowledge source, constructs the index-empirical knowledge base structure, and introduces the ternary function of support degree, nonsupport degree and hesitation degree to express the uncertainty of expert evaluation. In the reasoning process, the intuitionistic fuzzy distance method is used to match the input data with the knowledge rules, and the optimal empirical output is selected through the multilevel discriminative strategy. At the same time, the system introduces the inference feedback mechanism to realize the dynamic confidence adjustment and versioning management of knowledge rules. In this paper, the hardware and software architecture design of the expert system, data platform synergy mechanism, knowledge extraction and reasoning mechanism design are given in detail, and the effectiveness and interpretability of the system in actual fault diagnosis scenarios are verified through examples. The results show that the system can realize the structured management and effective use of expert experience, and improve the accuracy and automation level of distribution capacity regulating transformer health state assessment. The study provides theoretical and engineering references for constructing an intelligent power diagnosis system with adaptive capability.