A novel coriolis mass flowmeter signal processing method based on adaptive notch filter and Hilbert transform

Abstract

Coriolis mass flowmeter has been widely used in the energy field, and the key of mass flowrate measurement is to calculate the frequency and phase difference of the signal accurately. Aiming at the poor measurement precision problem in Coriolis mass flowmeter, a novel Coriolis mass flowmeter signal processing method is presented based on adaptive notch filter and Hilbert transform. Firstly, the long time continuous frequency tracking and accuracy problem of adaptive notch filter is effectively solved, by introducing the idea of negative feedback control. Then, the frequency estimation results are used to judgment whether the whole data will be extended or not, which makes the length of data sequence close to or equal to an integer multiple of the period. And then, Hilbert transform is conducted to the extended signals. Finally, the phase difference can be obtained by utilizing the sinusoidal functions. Simulation results show that the proposed method has high frequency and phase difference estimation accuracy, and it can be used for real time flowrate measurement of flowmeter. Experimental tests validate that the precision of this method is less than 3‰, which is more than 2 times of that of the traditional method.

Keywords

• Hilbert transform
• Adaptive notch filter
• Parameter estimation
• Coriolis mass flowmeter
• Flowrate measurement