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Faced with the constantly expanding scale of the power grid and the increasingly complex external environment, the factors affecting the safe and stable operation of intelligent energy metering equipment are also increasing. Therefore, a smart energy metering equipment status automatic detection system based on IGA-BP neural network is designed. In hardware, design data acquisition module, signal processing module, data transmission module, and data analysis module. In the software, by collecting detection data from intelligent energy metering equipment, basic energy metering error, voltage fluctuation amplitude, current fluctuation amplitude, and power factor are selected as the state variables of intelligent energy metering equipment. An improved genetic algorithm backpropagation (IGA-BP) neural network is introduced to iteratively calculate the state variables and achieve automatic detection of intelligent energy metering equipment status. The experimental results show that the minimum detection time for the intelligent electric energy metering equipment using the designed system is 2 seconds, and the detection results are consistent with the actual results, fully confirming that the designed system has good equipment status detection efficiency and accuracy.