A study on accurate sensing of intelligent power metering box operation state based on fuzzy inference algorithm

In order to reduce interference of the complexity and uncertainty of the operating environment on the electric energy metering box in accurately perceiving its operating status, this study proposes an intelligent method for accurate perception of the operating status of the electric energy metering box based on fuzzy reasoning. First, establish an indicator system that covers the factors influencing the operation status of intelligent energy metering boxes and collect indicator data. Then, establish an adaptive network based fuzzy inference system (ANFIS). Using indicator data as input information, the input data are fuzzified using a membership function, defined based on minimum ambiguity and transformed into a fuzzy set. Afterward, using the fuzzy IF-THEN rule, the fuzzy set of the input data is mapped to the fuzzy set of the output result. With the help of the five-layer structure of the ANFIS network, precise perception of the operating status of intelligent energy metering boxes is achieved through steps such as fuzzy processing, rule inference, sequential normalization, defuzzification, and output calculation. The experimental results show that this method can obtain relevant data based on the constructed indicator system and accurately perceive different operating states. Compared with existing methods, this method has a lower fluctuation rate of state perception delay, better adaptability, and can achieve accurate perception under different load conditions.