Big Data Modeling and Analysis for Power Transmission Equipment: A Novel Random Matrix Theoretical Approach

IEEE Access

Yingjie Yan¹  Gehao Sheng¹  Xiuchen Jiang¹  Robert Caiming Qiu² 

[1] Department of Electrical Engineering, Shanghai Jiaotong University, Shanghai, China;Department of Electrical and Computer Engineering, Tennessee Technological University, Cookeville, TN, USA;

关键词: Big data analytics;    big data model;    power transmission equipment;    key state;    large dimensional random matrix;    the single ring law;   

DOI  :  10.1109/ACCESS.2017.2784841

来源: DOAJ

【 摘 要 】

This paper explores a novel idea for power equipment monitoring and finds that random matrix theory is suitable for modeling the massive data sets in this situation. Big data analytics are mined from those data. We extract the statistical correlation between key states and those parameters. In particular, the (empirical) eigenvalue spectrum distribution and the (theoretical) single ring law are derived from large-dimensional random matrices whose entries are modeled as time series. The radii of the single ring law are used as statistical analytics to characterize the measured data. The evaluation of key state and anomaly detection are accomplished through the comparison of those statistical analytics.

【 授权许可】

Unknown