A novel signal processing method for Coriolis mass flowmeter based on time-varying signal model

A novel signal processing method for Coriolis mass flowmeter (CMF) is proposed based on time-varying signal model. First, an adaptive lattice notch filter with the capability of tracking frequency variation is applied to filter the signal and calculate the frequency. Then the recursive DTFT algorithm with negative frequency contribution, which can largely shorten the convergence stage, is introduced into the calculation of real-time phase difference between two enhanced signals. Sampled data are intercepted by overlap windows with a small overlap length. With the frequency and phase difference obtained, the time delay between two signals is calculated and then the mass flowrate is derived. Simulation results show that the proposed method is obviously superior to the existing CMF signal processing methods based on time-varying signal model.