Correction Method for Temperature Drift and Geomagnetic Field of TMR Current Sensor Based on Improved Deep Belief Network

被引：0
|
作者：
Yang T. [1 ]
Zhang Z. [1 ]
Liu Y. [1 ]
Wang L. [2 ]
机构：
[1] School of Electrical and Information Engineering, Tianjin University, Tianjin
[2] Electric Power Research Institute of Henan Electric Power Company of State Grid, Zhengzhou
来源：
Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology | 2021年 / 54卷 / 08期
基金：
中国国家自然科学基金;
关键词：
ADAM; Deep belief network; Geomagnetic field; Temperature drift; Tunnel magnetoresistance(TMR)current sensor;
D O I：
10.11784/tdxbz202009089
中图分类号：
学科分类号：
摘要：
Accurate current measurement is an essential prerequisite for lean power grid operation. The high-sensitivity and high-precision TMR current sensor has effectively enhanced the current measurement capability. Simultaneously, the influence of temperature drift and space geomagnetic field in the measurement process of TMR current sensor needs to be considered. To solve this problem, a correction method for temperature drift and geomagnetic field of TMR current sensor based on improved deep belief network is proposed. First, for the abnormal output data of the TMR current sensor because of strong magnetic field interference or failure, Bayesian combined with information entropy theory is used to identify and eliminate; second, the improved deep belief network is used to reconstruct the mapping relationship between the spatial geomagnetic field, temperature, and the measurement output of the TMR current sensor; finally, the calibration experiment and error analysis of the developed TMR current sensor are conducted. The experimental results show that within the temperature range of-40-80℃, the temperature drift coefficient after algorithm compensation is reduced from 900×10-6/℃ to 32.33×10-6/℃. The sensitivity of the TMR current sensor to the geomagnetic field is significantly reduced, the average absolute percentage error is reduced from 2.1530% to 0.4109%, and the root mean square error is reduced from 0.1048A to 0.0200A. © 2021, Editorial Board of Journal of Tianjin University(Science and Technology). All right reserved.
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页码：875 / 880
页数：5
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