4.5 Article

A Novel Phase Difference Measurement Method for Coriolis Mass Flowmeter Based on Correlation Theory

期刊

ENERGIES
卷 15, 期 10, 页码 -

出版社

MDPI
DOI: 10.3390/en15103710

关键词

Coriolis mass flowmeter; phase difference; correlation method; Hilbert transformation; adaptive notch filter

资金

  1. Natural Science Foundation of Chongqing, China [cstc2019jcyjmsxmX0628, cstc2019jcyj-msxmX0268]
  2. project of science and technology research program of Chongqing Education Commission of China [KJQN202112902]

向作者/读者索取更多资源

A new phase difference measurement method for Coriolis mass flowmeter is proposed based on correlation theories, aiming to solve the poor precision problem in phase difference measurements in engineering practice. The method estimates the signal frequency using an adaptive notch filter, conducts Hilbert transformation on the extended signals, and computes the correlation functions. Compared to traditional methods, the proposed method is suitable for both integer period and non-integer period sampling signals, and demonstrates superior accuracy, real-time performance, and dynamic performance.
Aiming at the poor precision problem in phase difference measurements with unknown frequencies in engineering practice, a new phase difference measurement method is proposed for Coriolis mass flowmeter based on correlation theories. Firstly, the signal frequency was estimated by using an adaptive notch filter, which was applied to filter the waves and determined the integer period of the sampling signals, and the non-integer period sampling signals needed to be extended. Then, the Hilbert transformation was conducted relative to the extended signals, and the correlation functions of these extended signals with the transformed signals can be computed. Finally, the formula of phase difference can be obtained by utilizing the sinusoidal function. Compared to traditional methods, such as the correlation method, the Hilbert transformation method, and sliding Goertzel algorithm, the proposed method is suitable for both integer period and non-integer period sampling signals, and its accuracy, real-time, and dynamic performance is superior. Simulation and experiment results validate the superiority and effectiveness of the proposed method.

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