用电大数据分析与电表异常检测

Electricity Consumption Big Data Analysis and Abnormal Meter Detection

随着我国智能电表使用日臻成熟,对智能电表的监测越来越重要.通过对电表数据的采集、清洗,完成数据格式化.运用皮尔森相关系数分析以及K折交叉验证等方法,进行数据分析.通过采用深度学习时序模型进行预测研究,最终达到检测异常与故障识别.通过对异常电表的检测,可以延长正常电表的使用寿命,节省大量的资源.

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.The service time of normal meter can be prolonged by abnormal meters testing.This will lead to saving a lot of resources.