Design and Implementation of a High-Sensitivity Magnetic Sensing System Based on GMI Effect

被引:0
作者
Wu W. [1 ,2 ]
Xu M. [3 ]
Han C. [4 ]
Tang J. [2 ]
Xu J. [1 ]
Xu L. [1 ]
Qin M. [1 ]
机构
[1] Department of Electronic Engineering, Army Medical University, Chongqing
[2] Chongqing Medical and Pharmaceutical College, Chongqing
[3] Department of Intelligence Science and Technology, National University of Defense Technology, Changsha, Changsha
[4] Intelligent Game and Decision Lab, Beijing
来源
Journal of Beijing Institute of Technology (English Edition) | 2024年 / 33卷 / 03期
基金
中国国家自然科学基金;
关键词
GMI effect; high-sensitivity; magnetic field sensing system; segmented superposition algorithm;
D O I
10.15918/j.jbit1004-0579.2024.053
中图分类号
学科分类号
摘要
A high-sensitivity magnetic sensing system based on giant magneto-impedance (GMI) effect is designed and fabricated. The system comprises a GMI sensor equipped with a gradient probe and an signal acquisition and processing module. A segmented superposition algorithm is used to increase target signal and reduce the random noise. The results show that under unshielded, room temperature conditions, the system achieves successful detection of weak magnetic fields down to 2 pT with a notable sensitivity of 1.84×108 V/T (G = 1 000). By applying 17 overlays, the segmented superposition algorithm increases the power proportion of the target signal at 31 Hz from 6.89% to 45.91%, surpassing the power proportion of the 2 Hz low-frequency interference signal. Simultaneously, it reduces the power proportion of the 20 Hz random noise. The segmented superposition process effectively cancels out certain random noise elements, leading to a reduction in their respective power proportions. This high-sensitivity magnetic sensing system features a simple structure, and is easy to operate, making it highly valuable for both practical applications and broader dissemination. © 2024 Beijing Institute of Technology. All rights reserved.
引用
收藏
页码:237 / 247
页数:10
相关论文
共 21 条
  • [1] Toga A. W., Mazziotta J. C., Brain mapping: the methods, pp. 227-253, (2002)
  • [2] Sternickel K., Braginski A. I., Biomagnetism using squids: status and perspectives, Super-conductor Science and Technology, 19, 3, pp. S160-S171, (2006)
  • [3] Mahdi A. E., Panina L. V., Mapps D., Some new horizons in magnetic sensing: High-Tc SQUIDs GMR and GMI materials, Sensors and Actuators A: Physical, 105, pp. 271-285, (2003)
  • [4] Zheng D. N., Superconducting quantum interference devices, Acta Physica Sinica, 70, 1, (2021)
  • [5] Boto E., Holmes N., Leggett J., Roberts G., Shah V., Meyer S. S., Munoz L. D., Mullinger K. J., Tierney T. M., Bestmann S., Barnes G. R., Bowtell R., Brookes M. J., Moving magnetoencephalography towards real-world applications with a wearable system, Nature, 555, 7698, pp. 657-661, (2018)
  • [6] Kim K., Begus S., Xia H., Lee S., Jazbinsek V., Trontelj Z., Romalis M. V., Multi-channel atomic magnetometer for magnetoencephalography: A configuration study, NeuroImage, 89, pp. 143-151, (2014)
  • [7] Borna A., Carter T. R., Goldberg J. D., Colombo1 A. P., Jau1 Y., Berry C., McKay J., Stephen J., Weisend M., Schwindt P. D. D., A 20-channel magnetoencephalography system based on optically pumped magnetometers, Physics in Medicine and Biology, 62, 23, pp. 8909-8923, (2017)
  • [8] Du P., Li J., Yang S., Yang S., Wang X., Zhou Y., Wang F., Wang R., Observing the steady-state visual evoked potentials with a compact quad-channel spin exchange relaxation-free magnetometer, Chinese Physics B, 28, 4, (2019)
  • [9] Chong L., Lei J., Yang Z., Wang T., Zhou Y., A low power micro fluxgate sensor with improved magnetic core, Microsystem Technologies, 19, 4, pp. 591-598, (2013)
  • [10] Shen H., Hu L., Fu X., Integrated Giant Magnetoresistance Technology for Approachable Weak Biomagnetic Signal Detections, Sensors, 18, 1, (2018)