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Non-invasive Ultrasound Doppler Effect Based Method of Liquid Flow Velocity Estimation in Pipe

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper discusses the estimation of flow velocity from a multi-sensor scenario. Different estimation methods were used, which allow the effective measurement of the actual Doppler shift in a noisy environment, such as water with air bubbles, and on this basis the estimation of the flow velocity in the pipe was calculated. Information fusion is proposed for the estimates collected. The proposed approach focuses on the density of the fluid. The proposed method is capable of determining the flow velocity with high accuracy and small variations. Simulation results for plastic and steel (both galvanized and non-galvanized) pipes show the possibility of accurate fluid flow measurements without the need for sensors inside the pipe.
Słowa kluczowe
Rocznik
Strony
141--148
Opis fizyczny
Bibliogr. 25 poz., fot., rys., tab., wykr.
Twórcy
  • Faculty of Electronics, Photonics and Microsystems, Department of Acoustics, Multimedia and Signal Processing Wroclaw University of Science and Technology Wrocław, Poland
  • Faculty of Electronics, Photonics and Microsystems, Department of Acoustics, Multimedia and Signal Processing Wroclaw University of Science and Technology Wrocław, Poland
  • Faculty of Electronics, Photonics and Microsystems, Department of Acoustics, Multimedia and Signal Processing Wroclaw University of Science and Technology Wrocław, Poland
Bibliografia
  • 1. Atkins M.D. (2016), Velocity field measurement using particle image velocimetry (PIV), [in:] Application of Thermo-Fluidic Measurement Techniques, Kim T., Lu T.J., Song S.J. [Eds.], pp. 125-166, doi: 10.1016/B978-0-12-809731-1.00005-8.
  • 2. Avilán E.J., Reis V., Barreira L.E., Salgado C.M. (2013), Evaluation of cross correlation technique to measure flow in pipes of the oil industry, [in:] 2013 International Nuclear Atlantic Conference – INAC 2013.
  • 3. Bar-Shalom Y., Li X.-Rong, Kirubarajan T. (2004), Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software, John Wiley & Sons.
  • 4. Beck M.S., Plaskowski A. (1987), Cross Correlation Flowmeters, Their Design and Application, Taylor & Francis.
  • 5. Buermans J., Lampa J., Lemon D. (2009), Turbine flow measurement in low-head plants – Acoustic scintillation flow meter: Why? How? Where?, Medicine, Corpus ID: 113046881.
  • 6. Cochran S. (2001), Ultrasonic instruments & devices – reference for modern instrumentation, techniques and technology, Ultrasound in Medicine and Biology, 27(10): 1439, doi: 10.1016/S0301-5629(01)00386-6.
  • 7. Cui Z. et al. (2016), A review on image reconstruction algorithms for electrical capacitance/resistance tomography, Sensor Review, 36(4): 429-445, doi: 10.1108/SR-01-2016-0027.
  • 8. Doran P.M. (2013), Bioprocess engineering principles, 2n ed., Academic Press Waltham.
  • 9. Grewal M.S., Andrews A.P. (2001), Kalman Filtering: Theory and Practice Using MATLAB, 2nd ed., John Wiley & Sons.
  • 10. Jazwinski A.H. (1970), Stochastic Processes and Filtering Theory, Elsevier Science.
  • 11. Jones F.E (1995), Techniques and topics in flow measurement, CRC Press.
  • 12. Kaipio J.P. et al. (2015), Process tomography and estimation of velocity fields, [in:] Industrial Tomography, Wang M. [Ed.], pp. 551-590, Woodhead Publishing, doi: 10.1016/B978-1-78242-118-4.00021-6.
  • 13. Kang L. et al. (2019), Flow velocity measurement using a spatial averaging method with two-dimensional flexural ultrasonic array technology, Sensors, 19(21): 4786, doi: 10.3390/s19214786.
  • 14. Lucas G.P., Cory J., Waterfall R.C., Loh W.W., Dickin F.J. (1999), Measurement of the solids volume fraction and velocity distributions in solids-liquid flows using dual-plane electrical resistance tomography, Flow Measurement and Instrumentation, 10(4): 249-258, doi: 10.1016/S0955-5986(99)00010-2.
  • 15. Lyons R. (2004), Understanding Digital Signal Processing, 2nd ed., Pearson Education Incorporated.
  • 16. Maybeck P.S. (1982), Stochastic Models, Estimation and Control: Volume 2, Academic Press.
  • 17. Matani A., Oshiro O., Chihara K. (1996), Doppler signal processing of blood flow using a wavelet transform, Japanese Journal of Applied Physics, 35(5S), doi: 10.1143/jjap.35.3131.
  • 18. Mori M., Tezuka K., Aritomi M., Kukura H., Takeda Y. (2004), Industrial application experiences of new type flow-metering system based on ultrasonic-Doppler flow velocity-profile measurement, [in:] Fourth International Symposium on Ultrasonic Doppler Methods for Fluid Mechanics and Fluid Engineering, Japan.
  • 19. Raffel M., Willert C.E., Kompenhans J. (1998), Particle Image Velocimetry: A Practical Guide, Springer Berlin, doi: 10.1007/978-3-662-03637-2.
  • 20. Särkkä S. (2006), Recursive Bayesian Inference on Stochastic Differential Equations, Helsinki University of Technology, Laboratory of Computational Engineering Publications, Report B54, ISBN: 951-22-8127-9.
  • 21. Solero G., Beghi M. (1995), Experimental fluid dynamic characterization of a premixed natural gas burner for domestic and semi-industrial applications, [in:] The Institute of Energy’s Second International Conference on Combustion & Emissions Control, pp. 39-48, doi: 10.1016/B978-0-902597-49-5.50007-X.
  • 22. Takeda Y. (1995), Instantaneous velocity profile measurement by ultrasonic Doppler method, JSME International Journal Series B Fluids and Thermal Engineering, 38(1): 8-16, doi: 10.1299/jsmeb.38.8.
  • 23. Takeda Y. (2012), Ultrasonic Doppler Velocity Profiler for Fluid Flow, Fluid Mechanics and its Applications, Springer, ISBN: 978-4-431-54026-7.
  • 24. Xu Y., Wang H., Cui Z., Dong F. (2009), Application of electrical resistance tomography for slug flow measurement in gas/liquid flow of horizontal pipe, [in:] 2009 IEEE International Workshop on Imaging Systems and Techniques, pp. 319-323, doi: 10.1109/IST.2009.5071657.
  • 25. Wu J. (2018), Acoustic streaming and its applications, Fluids, 3(4): 108, doi: 10.3390/fluids3040108.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023). (PL).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d600b529-4bae-41e2-b172-a1de7f4d76a0
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