Big Data Detection System of Electric Meter Based on Deep Learning Technology

摘要

With the sustained development of power plant of China, the installed base of electric meter grows gradually. It is more and more important to monitor smart meters with their mature use. The data formatting is completed through the collecting and cleaning to the data from meters. The data analysis is done by the methods including Pearson correlation coefficient analysis and K fold cross validation etc. Eventually testing abnormity and failure recognition can be obtained through prediction research based on deep learning time series model. Based on electric meter running big data analysis, the electric meter situation including normal and abnormal (error or electricity stealing) and relevant position can be obtained so as to take further action. The research and application of the testing system can avoid physical testing to electric meter. The service time of normal meter can be prolonged by abnormal meters testing. This will lead to saving a lot of resources.

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