Error Evaluation Method of ElectronicTransformer Based on Large Dimensional Random Matrices
- Resource Type
- Conference
- Authors
- Fan, Jie; Ma, Keqi; Xu, Minrui; Chen, Wenguang; Wu, Qiao; Lu, Zigang; Cheng, Hanmiao; Xu, Yangyang
- Source
- 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), 2019 IEEE 3rd. :372-376 Mar, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Engineered Materials, Dielectrics and Plasmas
Robotics and Control Systems
Covariance matrices
Gaussian distribution
Sparse matrices
Eigenvalues and eigenfunctions
Standards
Biological system modeling
Probability density function
Electronic transformer
Error state evaluation
Large dimensional random matrix
- Language
Error state evaluation of the electronic transformer (ET) in operation without the standard transformer is a conundrum in metrology. In this paper, an error state evaluation method of ET based on large dimensional random matrix theory is proposed. The similarity of the probability density function (PDF) and the eigenvalue moment statistics are used as the criteria for error evaluation. The distribution characteristics of the parameters served as matrix elements are described. The sparse matrix extension is achieved by data replication with Gaussian noise. Finally, based on the simulated data and the measured data, the effectiveness of the error evaluation method is verified. The results show that significant differences can be seen in this way when the error is 0.1%. The error state of the ET can be evaluated with the proposed method in real time.