A New Method for Phase Difference Estimation Based on Time-Varying Signal Model

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

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An improved signal processing method for Coriolis mass flowmeter based on time-varying signal model

Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788) ◽

10.1109/wcica.2004.1343316 ◽

2004 ◽

Cited By ~ 3

Author(s):

Wei Ni ◽

Kejun Xu

Keyword(s):

Signal Processing ◽

Processing Method ◽

Time Varying ◽

Signal Model ◽

Mass Flowmeter ◽

Signal Processing Method ◽

Coriolis Mass Flowmeter

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

2008 7th World Congress on Intelligent Control and Automation ◽

10.1109/wcica.2008.4593981 ◽

2008 ◽

Cited By ~ 2

Author(s):

Haitao Zhang ◽

Yaqing Tu ◽

Liangbing Liu ◽

Penghui Niu

Keyword(s):

Signal Processing ◽

Processing Method ◽

Time Varying ◽

Signal Model ◽

Mass Flowmeter ◽

Signal Processing Method ◽

Coriolis Mass Flowmeter

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A time-varying signal processing method for Coriolis mass flowmeter based on adaptive filter

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331216652955 ◽

2016 ◽

Vol 40 (1) ◽

pp. 261-268 ◽

Cited By ~ 2

Author(s):

Feng Dan ◽

Fan Shangchun ◽

Zheng Dezhi

Keyword(s):

Signal Processing ◽

Adaptive Filter ◽

Processing Method ◽

Time Varying ◽

Mean Square ◽

Least Mean Square ◽

Mass Flowmeter ◽

Signal Processing Method ◽

Coriolis Mass Flowmeter ◽

Nlms Algorithm

In this paper, the normalized least mean square (NLMS) algorithm, a time-varying signal processing method, is employed in a Coriolis mass flowmeter (CFM) to improve its weak anti-jamming capability. Initially, the fundamental principles of the NLMS algorithm adopted in the adaptive filter are analysed. Then, the NLMS algorithm is applied to analyse the signal processing of the CFM at different flow rates in experiments. By comparing several performance indicators and spectrum diagrams from being filtered by the NLMS algorithm and the least mean square (LMS) algorithm, the results indicate that the NLMS algorithm can lead to a better anti-jamming capability and reduce the influence of noise efficiently for the CFM. In addition, the NLMS method has a faster convergence speed and fewer stable errors than the LMS method. Therefore, the NLMS can improve the quality of the output signal of the CFM.

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A novel time varying signal processing method for Coriolis mass flowmeter

Review of Scientific Instruments ◽

10.1063/1.4884898 ◽

2014 ◽

Vol 85 (6) ◽

pp. 065116 ◽

Cited By ~ 10

Author(s):

Ting-Ao Shen ◽

Ya-Qing Tu ◽

Hai-Tao Zhang

Keyword(s):

Signal Processing ◽

Processing Method ◽

Time Varying ◽

Mass Flowmeter ◽

Signal Processing Method ◽

Coriolis Mass Flowmeter

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A Novel Method Based on Hilbert Transform for Signal Processing of Coriolis Mass Flowmeter

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001418580016 ◽

2017 ◽

Vol 32 (02) ◽

pp. 1858001 ◽

Cited By ~ 3

Author(s):

Wei Lin ◽

Jing-Lei Zhao

Keyword(s):

Signal Processing ◽

Phase Difference ◽

Mass Flow ◽

Hilbert Transform ◽

Processing System ◽

Tracking Accuracy ◽

Signal Processing System ◽

Mass Flowmeter ◽

Coriolis Mass Flowmeter ◽

Novel Method

The signal phase differences of Coriolis sensor and the mass flow are proportional. To improve the measurement accuracy of flow signal processing for Coriolis mass flowmeter, a novel method based on Hilbert Transform algorithm was proposed. The main method is as follows, two signals enhanced by LZ-filter with noise-canceling were considered as Hilbert Transform, then, the phase difference of the two filtered signals was calculated by a triangle characteristic of sin function. Synchronously, the instantaneous frequency was estimated by the structure of the analytical signal. Finally, the mass flow value was obtained by calculating the phase difference. The simulation experiments and Digital Signal Processing system (DSP) verification testing demonstrate that the new signal processing method, which is the LZ algorithm, has better characteristics of real-time and high-precision than the others. The experimental results show that the accuracy of phase difference measurement is 0.02% and the tracking accuracy of frequency is better than 0.07%.

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