Pang Na, Wang Dan, Yang Yuhan, Wang Rui
College of Computer Science and Technology, Beihua University, No. 3999 East Binjiang Road, Jilin 132013, China.
Sensors (Basel). 2023 Nov 16;23(22):9223. doi: 10.3390/s23229223.
During the measurement of magnetic fields, Residence Time Difference (RTD)-fluxgate sensors suffer from abnormal time difference jumps due to the random interference of magnetic core noise and environmental noise, which results in gross errors. This situation restricts the improvement of sensor accuracy and stability. In order to solve the above problems efficiently, a time difference gross error processing method based on the combination of the Mahalanobis distance (MD) and group covariance is presented in this paper, and the processing effects of different methods are compared and analyzed. The results of the simulation and experiment indicate that the proposed method is more advantageous in identifying the gross error in time difference. The signal-to-noise ratio for the time difference is improved by about 34 times, while the fluctuation of the Negative Magnetic Saturation Time (NMST) Δ is reduced by 95.402%, which significantly reduces the fluctuation of time difference and effectively improves the accuracy and stability of the sensor.
在磁场测量过程中，驻留时间差（RTD）磁通门传感器会因磁芯噪声和环境噪声的随机干扰而出现异常的时间差跳变，从而导致粗大误差。这种情况限制了传感器精度和稳定性的提高。为了有效解决上述问题，本文提出了一种基于马氏距离（MD）和组协方差相结合的时间差粗大误差处理方法，并对不同方法的处理效果进行了比较和分析。仿真和实验结果表明，该方法在识别时间差粗大误差方面更具优势。时间差的信噪比提高了约34倍，同时负磁饱和时间（NMST）Δ的波动降低了95.402%，显著减小了时间差的波动，有效提高了传感器的精度和稳定性。
