Signal processing precision of Coriolis mass flowmeters affects the measurement accuracy directly. To improve the measurement accuracy of Coriolis mass flowmeters, a phase and frequency matching-based signal processing method for Coriolis mass flowmeters is proposed. Estimated phase difference is obtained by means of frequency estimation, 90° phase shift, generating reference signals and cross-correlation. Simulated results demonstrate that the proposed method has better phase difference estimation and anti-interference performance than the Hilbert transform method, cross-correlation method, data extension-based correlation method, and quadrature delay estimator. Measurement results of Coriolis mass flowmeters verify the effectiveness and superiority of the proposed method in practice.
For the ultra-low frequency signals or adjacent Nyquist frequency signals, which exist in the vibration engineering domain, the traditional DTFT-based algorithm shows serious bias for phase difference measurement. It is indicated that the spectrum leakage and negative frequency contribution are the essential causes of the bias. In order to improve the phase difference measurement accuracy of the DTFT-based algorithm, two new sliding DTFT algorithms for phase difference measurement based on a new kind of windows are proposed, respectively. Firstly, the new kind of windows developed by convolving conventional rectangular windows is introduced, which obtains a stronger inhibition of spectrum leakage. Then, with negative frequency contribution considered, two new formulas for phase difference calculation under the new kind of windows are derived in detail. Finally, the idea of sliding recursive is proposed to decrease the computational load. The proposed algorithms are easy to be realized and have a higher accuracy than the traditional DTFT-based algorithm. Simulations and engineering applications verified the feasibility and effectiveness of the proposed algorithms.
In this paper, we focus on CMF signal processing and aim to resolve the problems of precision sharp-decline occurrence when using adaptive notch filters (ANFs) for tracking the signal frequency for a long time and phase difference calculation depending on frequency by the sliding Goertzel algorithm (SGA) or the recursive DTFT algorithm with negative frequency contribution. A novel method is proposed based on feedback corrected ANF and Hilbert transformation. We design an index to evaluate whether the ANF loses the signal frequency or not, according to the correlation between the output and input signals. If the signal frequency is lost, the ANF parameters will be adjusted duly. At the same time, singular value decomposition (SVD) algorithm is introduced to reduce noise. And then, phase difference between the two signals is detected through trigonometry and Hilbert transformation. With the frequency and phase difference obtained, time interval of the two signals is calculated. Accordingly, the mass flow rate is derived. Simulation and experimental results show that the proposed method always preserves a constant high precision of frequency tracking and a better performance of phase difference measurement compared with the SGA or the recursive DTFT algorithm with negative frequency contribution