Hu Jinghua, Pan Mengchun, Hu Jiafei, Li Sizhong, Chen Dixiang, Tian Wugang, Sun Kun, Du Qingfa, Wang Yuan, Pan Long, Zhou Weihong, Zhang Qi, Li Peisen, Peng Junping, Qiu Weicheng, Zhou Jikun
College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China.
Institute of Systems Engineering, China Academy of Engineering Physics, Mianyang 621900, China.
Rev Sci Instrum. 2017 Sep;88(9):095006. doi: 10.1063/1.5003618.
Magnetic modulation methods especially Micro-Electro-Mechanical System (MEMS) modulation can improve the sensitivity of magnetoresistive (MR) sensors dramatically, and pT level detection of Direct Current (DC) magnetic field can be realized. While in a Low Frequency Alternate Current (LFAC) magnetic field measurement situation, frequency measurement is limited by a serious spectrum aliasing problem caused by the remanence in sensors and geomagnetic field, leading to target information loss because frequency indicates the magnetic target characteristics. In this paper, a compensation field produced with integrated coils is applied to the MR sensor to remove DC magnetic field distortion, and a LFAC magnetic field frequency estimation algorithm is proposed based on a search of the database, which is derived from the numerical model revealing the relationship of the LFAC frequency and determination factor [defined by the ratio of Discrete Fourier Transform (DFT) coefficients]. In this algorithm, an inverse modulation of sensor signals is performed to detect jumping-off point of LFAC in the time domain; this step is exploited to determine sampling points to be processed. A determination factor is calculated and taken into database to figure out frequency with a binary search algorithm. Experimental results demonstrate that the frequency measurement resolution of the LFAC magnetic field is improved from 12.2 Hz to 0.8 Hz by the presented method, which, within the signal band of a magnetic anomaly (0.04-2 Hz), indicates that the proposed method may expand the applications of magnetoresistive (MR) sensors to human healthcare and magnetic anomaly detection (MAD).
磁调制方法，特别是微机电系统（MEMS）调制，可以显著提高磁阻（MR）传感器的灵敏度，并实现皮特斯拉（pT）级直流（DC）磁场检测。然而，在低频交变电流（LFAC）磁场测量情况下，由于传感器中的剩磁和地磁场导致严重的频谱混叠问题，频率测量受到限制，这会导致目标信息丢失，因为频率指示了磁性目标的特征。本文将集成线圈产生的补偿场应用于MR传感器以消除直流磁场畸变，并基于数据库搜索提出了一种LFAC磁场频率估计算法，该数据库来自揭示LFAC频率与判定因子[由离散傅里叶变换（DFT）系数之比定义]关系的数值模型。在该算法中，对传感器信号进行逆调制以在时域中检测LFAC的跳变点；利用这一步骤确定要处理的采样点。计算判定因子并将其存入数据库，然后用二分搜索算法算出频率。实验结果表明，所提方法将LFAC磁场的频率测量分辨率从12.2 Hz提高到了0.8 Hz，这表明在所提方法在磁异常（0.04 - 2 Hz）的信号频段内，该方法可能会将磁阻（MR）传感器的应用扩展到人类医疗保健和磁异常检测（MAD）领域。
