Abstract
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.
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