Excitation Processing of Self-Oscillating Fluxgate Based on Improved Empirical Wavelet Transform

Self-oscillating fluxgates are widely used in current measurements because of their advantages in cost and other factors. And the excitation processing can play an important role in affecting the sensors' performance. This paper proposes to apply the improved empirical wavelet transform (IEWT) to the exciting signal processing of self-oscillating fluxgate to achieve adaptive demodulation and effective filtering. And to adjust the characteristic of exciting current, the paper uses frequency domain envelope processing to achieve an accurate selection of the main frequency points. The extraction of the detected signal in the low-frequency band is accomplished by the sub-band weights set. The exciting current is adaptively decomposed into several modes by the IEWT, and the low-frequency mode can directly correspond to the detected current, while the high-frequency mode can accurately determine the saturation of the magnetic core. The feasibility of the method is demonstrated by the simulation.