A time-varying signal processing method for Coriolis mass flowmeter
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Abstract:
The mass flowrate of Coriolis mass flowmeter in practical application has slow changes with time. To solve the problem, an improved time-varying signal model whose frequency, amplitude and phase are time-varying based on the random walk model is established firstly. A new algorithm of adaptive notch filter with the capability of tracking frequency variation is applied to filter the sensor output signal of Coriolis mass flowmeter and its frequency is calculated next. An adaptive line enhancer based on the mentioned notch filter extracts fundamental frequency signal from noisy data. Then, by short window intercepting, the revised sliding DTFT recursive algorithm is introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and phase difference obtained, the time interval between the two signals is calculated and then the mass flowrate is derived. The simulations and field test results show that the proposed method can not only track the change of frequency and phase, but also ensure the calculation accuracy when measuring small phase difference. The computational load of the algorithm is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.
