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Optical Engineering

Investigation of optical current transformer signal processing method based on an improved Kalman algorithm
Author(s): Yan Shen; Jin-ming Ge; Guo-qing Zhang; Wen-bin Yu; Rui-tong Liu; Wei Fan; Ying-xuan Yang
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Paper Abstract

This paper explores the problem of signal processing in optical current transformers (OCTs). Based on the noise characteristics of OCTs, such as overlapping signals, noise frequency bands, low signal-to-noise ratios, and difficulties in acquiring statistical features of noise power, an improved standard Kalman filtering algorithm was proposed for direct current (DC) signal processing. The state-space model of the OCT DC measurement system is first established, and then mixed noise can be processed by adding mixed noise into measurement and state parameters. According to the minimum mean squared error criterion, state predictions and update equations of the improved Kalman algorithm could be deduced based on the established model. An improved central difference Kalman filter was proposed for alternating current (AC) signal processing, which improved the sampling strategy and noise processing of colored noise. Real-time estimation and correction of noise were achieved by designing AC and DC noise recursive filters. Experimental results show that the improved signal processing algorithms had a good filtering effect on the AC and DC signals with mixed noise of OCT. Furthermore, the proposed algorithm was able to achieve real-time correction of noise during the OCT filtering process.

Paper Details

Date Published: 19 January 2018
PDF: 11 pages
Opt. Eng. 57(1) 013103 doi: 10.1117/1.OE.57.1.013103
Published in: Optical Engineering Volume 57, Issue 1
Show Author Affiliations
Yan Shen, Harbin Institute of Technology (China)
Jin-ming Ge, Harbin Institute of Technology (China)
Guo-qing Zhang, Harbin Institute of Technology (China)
Wen-bin Yu, Harbin Institute of Technology (China)
Rui-tong Liu, Liaoning Electric Power Co., Ltd. (China)
State Grid Electric Power Research Institute (China)
Wei Fan, Liaoning Electric Power Co., Ltd. (China)
State Grid Electric Power Research Institute (China)
Ying-xuan Yang, State Grid Electric Power Research Institute (China)
Liaoning Electric Power Co Ltd (China)


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