Research on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method
As a new generation of magnetic sensors, tunnel magnetoresistive sensors have the advantages of good temperature characteristics and high sensitivity and have been extensively studied and applied in electric energy measurement. External magnetic field interference is an important essential factor af...
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2021
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oai:doaj.org-article:ac1662db0e054a059f34fa5d608797ff2021-11-26T04:33:12ZResearch on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method2352-484710.1016/j.egyr.2021.08.043https://doaj.org/article/ac1662db0e054a059f34fa5d608797ff2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352484721006454https://doaj.org/toc/2352-4847As a new generation of magnetic sensors, tunnel magnetoresistive sensors have the advantages of good temperature characteristics and high sensitivity and have been extensively studied and applied in electric energy measurement. External magnetic field interference is an important essential factor affecting the measurement accuracy of magnetic sensors. The article studies the measurement principle of the tunnel magnetoresistive sensor, establishes an array model with interference sources, and then proposes an improved adaptive filtering method based on the versoria variable step to suppress external magnetic field interference. Then specific to the DC distribution network’s current measurement scenario, the influence of the ratio of the interference source distance to the array radius and the initial angle of the array on the measurement error is analyzed. The interference suppression effects of different other algorithms are analyzed compared. Finally, it is verified by building finite element simulation and simulation tests. The research results show that when the measured current I1=300A, the interference current I2=-300A or I1=-300A, I2=300A, the relative error before filtering and after filtering based on the improved algorithm drops from 4.2907% to 0.02667%, which is much smaller than 1%. This provides a theoretical basis for tunneling magnetoresistance sensors to measure energy in the DC distribution network further.Jicheng YuChangxi YueChengzhou JiangDongdong ZhangXiaoning HuangChengshun YangLei LiElsevierarticleDC distribution networkTunnel magnetoresistanceSensor arrayVersieraImproved adaptive filteringExternal magnetic field interferenceElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENEnergy Reports, Vol 7, Iss , Pp 300-311 (2021) |
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DC distribution network Tunnel magnetoresistance Sensor array Versiera Improved adaptive filtering External magnetic field interference Electrical engineering. Electronics. Nuclear engineering TK1-9971 |
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DC distribution network Tunnel magnetoresistance Sensor array Versiera Improved adaptive filtering External magnetic field interference Electrical engineering. Electronics. Nuclear engineering TK1-9971 Jicheng Yu Changxi Yue Chengzhou Jiang Dongdong Zhang Xiaoning Huang Chengshun Yang Lei Li Research on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method |
description |
As a new generation of magnetic sensors, tunnel magnetoresistive sensors have the advantages of good temperature characteristics and high sensitivity and have been extensively studied and applied in electric energy measurement. External magnetic field interference is an important essential factor affecting the measurement accuracy of magnetic sensors. The article studies the measurement principle of the tunnel magnetoresistive sensor, establishes an array model with interference sources, and then proposes an improved adaptive filtering method based on the versoria variable step to suppress external magnetic field interference. Then specific to the DC distribution network’s current measurement scenario, the influence of the ratio of the interference source distance to the array radius and the initial angle of the array on the measurement error is analyzed. The interference suppression effects of different other algorithms are analyzed compared. Finally, it is verified by building finite element simulation and simulation tests. The research results show that when the measured current I1=300A, the interference current I2=-300A or I1=-300A, I2=300A, the relative error before filtering and after filtering based on the improved algorithm drops from 4.2907% to 0.02667%, which is much smaller than 1%. This provides a theoretical basis for tunneling magnetoresistance sensors to measure energy in the DC distribution network further. |
format |
article |
author |
Jicheng Yu Changxi Yue Chengzhou Jiang Dongdong Zhang Xiaoning Huang Chengshun Yang Lei Li |
author_facet |
Jicheng Yu Changxi Yue Chengzhou Jiang Dongdong Zhang Xiaoning Huang Chengshun Yang Lei Li |
author_sort |
Jicheng Yu |
title |
Research on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method |
title_short |
Research on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method |
title_full |
Research on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method |
title_fullStr |
Research on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method |
title_full_unstemmed |
Research on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method |
title_sort |
research on suppression of external magnetic field interference of tunnel magnetoresistive sensor based on versoria variable step improved adaptive filtering method |
publisher |
Elsevier |
publishDate |
2021 |
url |
https://doaj.org/article/ac1662db0e054a059f34fa5d608797ff |
work_keys_str_mv |
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1718409860499898368 |