A temperature compensation method for fiber optic current transformer based on Kalman filter

Abstract

The invention discloses a fiber current transformer temperature compensation method based on Kalman filtering, and the method comprises the following steps: S1, designing a temperature feature test scheme of a fiber current transformer, carrying out the fixed-point temperature testing of the fiber current transformer, and collecting a current data sequence {x1(t)}; S2, carrying out the preprocessing and statistic test of the current data sequence {x1(t)}; S3, building an AR time sequence model; S4, filtering the random noise in zero offset data of the fiber current transformer through employing the Kalman filtering; S5, carrying out the recognition of the structure and parameters of a temperature drift error model of the fiber current transformer and the model evaluation. The method can effectively carry out modeling according to the difference of drift impact on the fiber current transformer in different temperature sections through employing a plurality of segmented models, and improves the modeling precision and universality.

Description

technical field [0001] The invention relates to the field of temperature compensation of optical fiber current transformers, in particular to a method for temperature compensation of optical fiber current transformers based on Kalman filtering. Background technique [0002] The electronic transformer is an important process layer equipment in the smart substation, which provides current and voltage information for the bay layer equipment of the smart substation, and realizes functions such as power system relay protection, electric energy metering, fault recording, and status monitoring. Optical fiber current transformers realize real-time measurement and monitoring of current signals, and provide input signals for power system relay protection, electric energy metering and other equipment. Compared with electromagnetic current transformers, optical fiber current transformers have a series of advantages of high measurement accuracy, large dynamic range, wide frequency respon...

AI Technical Summary

Problems solved by technology

At present, in the establishment of the model for the output signal of the optical fiber current transformer, fixed models can be used, such as AR(2), ARMA(2,1), and then filtered, but the model statistical analysis of the output sequence of the optical fiber current transformer cannot be ignored , and the non-stationary, non-random and non-normal characteristics of the output sequence of the data analysis process, the output sequence is independently, stable, normal, zero-mean and trend item processing, and the direct use of the time series model analysis does not fundamentally It conforms to the characteristic that the time series is suitable for a stationary sequence, so the directly established model has a large error

Images