Abstract
As an increasingly popular flow metering technology, Coriolis mass flowmeter exhibits high measurement accuracy under single-phase flow condition and is widely used in the industry. However, under complex flow conditions, such as two-phase flow, the measurement accuracy is greatly decreased due to various factors including improper signal processing methods. In this study, three digital signal processing methods—the quadrature demodulation (QD) method, Hilbert method, and sliding discrete time Fourier transform method—are analyzed for their applications in processing sensor signals and providing measurement results under gas-liquid two-phase flow condition. Based on the analysis, specific improvements are applied to each method to deal with the signals under two-phase flow condition. For simulation, sensor signals under single- and two-phase flow conditions are established using a random walk model. The phase difference tracking performances of these three methods are evaluated in the simulation. Based on the digital signal processor, a converter program is implemented on its evaluation board. The converter program is tested under single- and two-phase flow conditions. The improved signal processing methods are evaluated in terms of the measurement accuracy and complexity. The QD algorithm has the best performance under the single-phase flow condition. Under the two-phase flow condition, the QD algorithm performs a little better in terms of the indication error and repeatability than the improved Hilbert algorithm at 160, 250, and 420 kg/h flow points, whereas the Hilbert algorithm outperforms the QD algorithm at the 600 kg/h flow point.
摘要
科里奥利质量流量计作为一种日益流行的流量测量仪表, 在单相流条件下表现出较高测量精度, 并在工业上得到广泛应用. 但在复杂流动条件下, 例如两相流工况, 由于各种因素 (包括不合适的信号处理方法), 测量精度会大大降低. 本文分析了3种数字信号处理方法——正交解调 (QD)、 希尔伯特和滑动离散傅立叶变换法, 分别用于处理传感器信号并在两相流工况下测试算法性能. 在此基础上, 分别改进了两相流条件下的信号处理方法. 在仿真中使用随机游走模型分别建立单相流和两相流工况下的传感器信号, 评估这3种方法的相位差跟踪性能. 基于数字信号处理器, 在其评估板上完成转换器程序设计. 将转换器在单相流和两相流工况下测试, 根据测量精度和算法复杂度评估改进的信号处理方法性能, 结果表明QD算法在单相流工况下性能最佳. 在两相流条件下, QD算法在160、 250和420 kg/h流量点的测量指示误差和重复性能优于改进的希尔伯特算法, 而希尔伯特算法在600 kg/h流量点的性能优于QD算法.
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References
Cage DR, 1988. Drive Means for Oscillating Flow Tubes of Parallel Path Coriolis Mass Flow Rate Meter. US Patent 473 814 4.
Carpenter BL, 1988. Ferromagnetic Drive and Velocity Sensors for a Coriolis Mass Flow Rate Meter. US Patent 477 783 3.
Fan LY, 1995. The description for staggered periodic sampling signal FIR filter in time and frequency domains. Acta Electron Sin, 23(9):70–74 (in Chinese).
Flecken P, 1989. Arrangement for Generating Natural Resonant Oscillations of a Mechanical Oscillating System. US Patent 480 189 7.
Huang DP, Wang JQ, Yu SD, et al., 2016. Research on the analog driving circuit of Coriolis mass flow meter. Autom Instrum, 31(1):71–76 (in Chinese). https://doi.org/10.19557/j.cnki.1001-9944.2016.01.018
Kalotay P, Bruck R, Emch A, et al., 1991. Flow Tube Drive Circuit Having a Bursty Output for Use in a Coriolis Meter. US Patent 500 910 9.
Kunze JW, Storm R, Wang T, 2014. Coriolis mass flow measurement with entrained gas. Proc Sensors and Measuring Systems, p.1–6.
Li M, Henry M, 2016. Signal processing methods for Coriolis mass flow metering in two-phase flow conditions. Proc IEEE Int Conf on Industrial Technology, p.690–695. https://doi.org/10.1109/icit.2016.7474833
Li M, Xu KJ, Hou QL, et al., 2010. Startup method of digital Coriolis mass flowmeter using alternating exciting of positive-negative step signal. Chin J Sci Instrum, 31(1):172–177 (in Chinese). https://doi.org/10.19650/j.cnki.cjsi.2010.01.030
Li XG, Xu KJ, 2009. Research on non-linear amplitude control method of Coriolis mass flow-tube. J Electron Meas Instrum, 23(6):82–86 (in Chinese).
Li Y, Xu KJ, Zhu ZH, et al., 2010. Study and implementation of processing method for time-varying signal of Coriolis mass flowmeter. Chin J Sci Instrum, 31(1):8–14 (in Chinese). https://doi.org/10.19650/j.cnki.cjsi.2010.01.002
Liu JR, Sun LJ, Wang HX, 2018. Signal processing of Coriolis mass flowmeters under gas-liquid two-phase flow conditions. Proc IEEE Int Instrumentation and Measurement Technology Conf, p.1–6. https://doi.org/10.1109/i2mtc.2018.8409623
Maginnis RL, 2003. Initialization Algorithm for Drive Control in a Coriolis Flowmeter. US Patent 650 513 5.
Mehendale A, 2008. Coriolis Mass Flow Rate Meters for Low Flows. PhD Thesis, University of Twente, Enschede, the Netherlands.
Meribout M, Saied IM, Hosani EA, 2018. A new FPGA-based terahertz imaging device for multiphase flow metering. IEEE Trans Terahertz Sci Technol, 8(4):418–426. https://doi.org/10.1109/TTHZ.2018.2824241
Meribout M, Shehaz F, Saied IM, et al., 2019. High gas void fraction flow measurement and imaging using a THz-based device. IEEE Trans Terahertz Sci Technol, 9(6): 659–668. https://doi.org/10.1109/TTHZ.2019.2945184
Röck H, Koschmieder F, 2009. Model-based phasor control of a Coriolis mass flow meter (CMFM) for the detection of drift in sensitivity and zero point. In: Mukhopadhyay SC, Gupta GS, Huang RY (Eds.), Recent Advances in Sensing Technology. Springer Berlin Heidelberg, p.221–240. https://doi.org/10.1007/978-3-642-00578-7_13
Romano P, 1990. Coriolis Mass Flow Rate Meter Having a Substantially Increased Noise Immunity. US Patent 493 419 6.
Shen TA, Tu YQ, Li M, et al., 2015. New sliding DTFT algorithm for phase difference measurement based on a new kind of windows and its analysis. J Centr South Univ, 46(4):1302–1309 (in Chinese). https://doi.org/10.11817/j.issn.1672-7207.2015.04.019
Shen TA, Li M, Li HN, et al., 2017. Phase difference estimation method for Coriolis mass flowmeter based on correlation and Hilbert transform. Chin J Sci Instrum, 38(12):2908–2914 (in Chinese).
Shimada H, 2013. Coriolis Flowmeter. US Patent 844 278 1.
Svete A, Kutin J, Bobovnik G, et al., 2015. Theoretical and experimental investigations of flow pulsation effects in Coriolis mass flowmeters. J Sound Vibr, 352:30–45. https://doi.org/10.1016/j.jsv.2015.05.014
Tao BB, Hou QL, Shi Y et al., 2014. Method and implementation of measuring the flow of liquid mixed with gas for Coriolis mass flowmeter. Chin J Sci Instrum, 35(8):1796–1802 (in Chinese). https://doi.org/10.19650/j.cnki.cjsi.2014.08.016
Tu YQ, Zhang HT, 2008. Method for CMF signal processing based on the recursive DTFT algorithm with negative frequency contribution. IEEE Trans Inst Meas, 57(11): 2647–2654. https://doi.org/10.1109/tim.2008.925006
Wang JH, 2013. Design of Coriolis Mass Flowmeter Based on Orthogonal Algorithm. MS Thesis, Shanghai Jiao Tong University, Shanghai, China (in Chinese).
Wang T, Baker R, 2014. Coriolis flowmeters: a review of developments over the past 20 years, and an assessment of the state of the art and likely future directions. Flow Meas Instrum, 40:99–123. https://doi.org/10.1016/j.flowmeasinst.2014.08.015
Yang HY, Tu YQ, Zhang HT, et al., 2012. Phase difference measuring method based on SVD and Hilbert transform for Coriolis mass flowmeter. Chin J Sci Instrum, 33(9): 2101–2107 (in Chinese). https://doi.org/10.3969/j.issn.0254-3087.2012.09.026
Yang JW, Jia MP, 2006. Study on processing method and analysis of end problem of Hilbert-Huang spectrum. J Vibr Eng, 19(2):283–288 (in Chinese). https://doi.org/10.3969/j.issn.1004-4523.2006.02.025
Yokoi T, Owada H, 1996. Coriolis Type Mass Flowmeter Utilizing Phase Shifters for Phase Shifting of the Output Signals. US Patent 557 876 4.
Zamora M, Henry MP, 2008. An FPGA implementation of a digital Coriolis mass flow metering drive system. IEEE Trans Ind Electron, 55(7):2820–2831. https://doi.org/10.1109/TIE.2008.925646
Zhang JG, Xu KJ, Fang ZY, et al., 2017. Applications of digital signal processing technology in Coriolis mass flowmeter. Chin J Sci Instrum, 38(9):2087–2102 (in Chinese). https://doi.org/10.3969/j.issn.0254-3087.2017.09.001
Acknowledgements
The authors would like to thank the technology support from both KROHNE UK and China. We would particularly like to acknowledge the discussion with Prof. Tao WANG from the University of Kent.
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Chunhui LI and Lijun SUN designed the research. Jiarong LIU and Haiyang LI processed the data. Chunhui LI drafted the manuscript. Jiarong LIU and Yang ZHANG helped organize the manuscript. Chunhui LI, Lijun SUN, and Huaxiang WANG revised and finalized the paper.
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Chunhui LI, Lijun SUN, Jiarong LIU, Yang ZHANG, Haiyang LI, and Huaxiang WANG declare that they have no conflict of interest.
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Project supported by the Scientific Research Project of Shanghai Municipal Bureau of Quality, China and the Technical Supervision Foundation of China (No. 2018-05)
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Li, C., Sun, L., Liu, J. et al. Improvement of signal processing in Coriolis mass flowmeters for gas-liquid two-phase flow. Front Inform Technol Electron Eng 22, 272–286 (2021). https://doi.org/10.1631/FITEE.1900558
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DOI: https://doi.org/10.1631/FITEE.1900558
Key words
- Coriolis mass flowmeter
- Digital signal processing method
- Two-phase flow condition
- Quadrature demodulation
- Sliding discrete time Fourier transform (SDTFT)
- Hilbert transform