EMF Signal Processing Scheme of Step Excitation Based on Data Fusion

Abstract

When using electromagnetic flowmeter (EMF) to measure slurry flow, the flow signal will fluctuate randomly due to slurry noise interference. In order to reduce the influence of slurry noise, this paper proposes a signal processing scheme based on data fusion. Firstly, through different amplitude demodulation methods, multiple sets of velocity data are obtained simultaneously. Then, a single set of flow data is pre-processed based on support degree. Finally, adaptive weighted fusion is performed on multiple sets of data. The paper conducted a comparison experiment between the data fusion scheme and the moving average median filtering scheme. Experiments show that the steady-state volatility of data fusion scheme is generally smaller. The signal fusion scheme based on data fusion can effectively overcome influence of slurry noise on flow signal of step excitation EMF.