Parallel Detection Method of Electric Energy Metering Instrument Anomaly Based on Big Data Communication Technology
With the development of big data technology,the power system has increasingly high requirements for the accuracy and reliability of electric energy metering instrument.Traditional methods for detecting anomalies in electric energy metering instrument often suffer from long response times and insufficient detection accuracy.To address these issues,a parallel anomaly detection method for electric energy metering instrument based on big data communication technology is proposed.This method combines Internet of Things sensors,fast Fourier transform,principal component analysis,and Apache Spark distributed computing framework to achieve real-time collection,preprocessing,feature extraction,and parallel detection of energy metering data,improving the accuracy and efficiency of anomaly detection and providing solid technical support for the stable operation and optimized management of power systems.
big data communicationelectric energy metering instrumentsabnormal parallel detection
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