Intelligent Energy Measurement Equipment Status Automatic Detection System Based on IGA-BP Neural Network
To address the growing challenges posed by the expanding power grid scale and increasingly complex external environ-ment,a study was conducted on the design of an intelligent electric energy metering equipment status automatic detection system based on the IGA-BP neural network.The hardware components of the system include a data acquisition module,a signal processing module,a data transmission module,and a data analysis module.In the software aspect,the system collects detection data from intel-ligent electric energy metering equipment and selects fundamental parameters such as metering error,voltage fluctuation,current fluctuation,and power factor as status indicators.An IGA-BP neural network is then employed to perform iterative calculations on these status indicators,enabling automatic detection of the equipmen's status.Experimental results demonstrate that the proposed system achieves a minimum detection time of 2 seconds for intelligent electric energy metering equipment,with the detection results a-ligning precisely with actual conditions.This verifies the systems high efficiency and accuracy in equipment status detection.
detection systemintelligent energy metering equipmentsensorsIGA-BP neural network modelstatus detection
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