Signal Processing Method for Coriolis Mass Flowmeter Based on Lattice Notch Filter and DTFT
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Abstract:
A novel signal processing method for Coriolis mass flowmeter is proposed based on time-varying signal model. First, an adaptive lattice notch filter is applied to filter the output signal, whose frequency, amplitude and phase are time-varying based on the random walk model, of Coriolis mass flowmeter to get its frequency and enhanced signal. Then, by short window intercepting, the DTFT algorithm with negative frequency contribution is introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference, the time interval between two signals is calculated. Simulation results show that the proposed method is efficient. Furthermore, the computation of algorithms is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.
