Information Analysis Method of Abnormal Data Under Intelligent Manufacturing Technology
In order to solve the problems of low calculation efficiency and insufficient detection accuracy of information analysis method of electricity data anomaly in the prior art,a new type of abnormal electricity data analysis system is designed.The system relies on local matrix reconstruction(LMR)to realize abnormal electric energy data detection,and characterizes the power consumption mode by using 5 daily load characteristics instead of high-dimensional daily load curves.Principal component analysis(PCA)is combined to calculate the weighted reconstruction error in the local range,and finally the reconstruction error of each sample is compared with its neighboring samples to calculate the local outlier score.The experimental results show that the system has high accuracy in processing abnormal electricity data with the error rate of only 4.2%upon applying 2 TB test data.The proposed method greatly improves the ability of information analysis of abnormal data.
intelligent manufacturingabnormal electricity datalocal matrix reconstructionprincipal component analysisintelligent electric energy meter
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