An adaptive error compensation method for wide-range current transformers based on segmentation and dimensionality reduction

This paper proposes an adaptive error compensation method for wide-range current transformers based on segmentation and dimensionality reduction. On the basis of the circular magnetic split compensation, a segmented aggregation approximation algorithm with a shift factor is used to reduce the dimensionality of the input signal, after which the gain of the compensation signal is further adjusted based on the idea of adaptive control to track the change of the error to achieve closed-loop measurement and extend the range. The validation results show that the error of the low-voltage current transformer for wide-range metering meets the 0.2SS level under both light and full load conditions.