An improved signal processing method for Coriolis mass flowmeter based on time-varying signal model

摘要

An adaptive IIR notch filter with the capability of tracking frequency variation was applied to filter the sensor output signal, whose frequency, amplitude and phase were time-varying based on the random walk model, of Coriolis mass flow meter and calculates its frequency. An adaptive line enhancer based on the above notch filter extracted the signal we required from noisy data. Then the sliding Goertzel algorithm with overlap windows was used to calculate the real time phase difference between two signals of this kind. With the frequency and phase difference obtained, the time interval of the two signals and the mass flowrate were derived. The simulation results show that algorithms studied in this paper are efficient.