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Time of Flights Estimations of Ultrasonic Signals Based on Numerical Methods

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Progress in Intelligent Decision Science (IDS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1301))

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Abstract

Flow measurement is of great importance in many industrial applications. Ultrasonic flow measurement using time-of-flight technique can equip adequate solutions for such processes. The estimation of time of flights of the ultrasonic signals has a key role in the measurement process under the case of ultrasonic signal technology. In this work, a robust technique is proposed based on numerical methods in order to estimate the time-of-flights of the ultrasonic signals. Due to the discrete nature of the ultrasonic signals, the proposed method shows efficient results in order to estimate the time of flights. The proposed method is validated through experimental works. According to the results, Lagrange-Taylor, Taylor (forward) numerical schemes supplied better performance over correlation based method at overall volumetric flow rates, respectively.

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References

  1. Angrisani, L., Baccigalupi, A., Moriello, R.S.L.: Ultrasonic-Based Distance Measurement Through Discrete Extended Kalman Filter. INTECH Open Access Publisher (2009)

    Google Scholar 

  2. Chen, X., Liu, C., Yang, D., Liu, X., Hu, L., Xie, J.: Highly accurate airflow volumetric flowmeters via pmuts arrays based on transit time. J. Microelectromech. Syst. 28(4), 707–716 (2019)

    Article  Google Scholar 

  3. Chhantyal, K., Jondahl, M.H., Viumdal, H., Mylvaganam, S.: Upstream ultrasonic level based soft sensing of volumetric flow of non-newtonian fluids in open venturi channels. IEEE Sens. J. 18(12), 5002–5013 (2018)

    Article  Google Scholar 

  4. Fernandez, J., Heller, P., Reinalter, W., Roger, M., Guillot, E.: Mass flow measurement and calibration procedures. Technical report (2014). https://doi.org/10.13140/RG.2.2.35021.23523

  5. Gerasimov, S., Zhelbakov, I.: Correlation analysis of probing signals as a special case of the digital signal processing methods in an ultrasonic liquid flow measurement applications. In: 2018 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), pp. 1–9. IEEE (2018)

    Google Scholar 

  6. Hitomi, J., Murai, Y., Park, H.J., Tasaka, Y.: Ultrasound flow-monitoring and flow-metering of air-oil-water three-layer pipe flows. IEEE access 5, 15021–15029 (2017)

    Article  Google Scholar 

  7. Huhn, F., Schanz, D., Gesemann, S., Dierksheide, U., van de Meerendonk, R., Schroder, A.: Large-scale volumetric flow measurement in a pure thermal plume by dense tracking of helium-filled soap bubbles. Exp. Fluids 58(9), 116 (2017)

    Article  Google Scholar 

  8. Jacovitti, G., Scarano, G.: Discrete time techniques for time delay estimation. IEEE Trans. Signal Process. 41(2), 525–533 (1993)

    Article  Google Scholar 

  9. Jia, J., Wang, H., Millington, D.: Electrical resistance tomography sensor for highly conductive oil-water two-phase flow measurement. IEEE Sens. J. 17(24), 8224–8233 (2017)

    Article  Google Scholar 

  10. Lin, Y., Hans, V.: Self-monitoring ultrasonic gas flow meter based on vortex and correlation method. IEEE Trans. Instrum. Meas. 56(6), 2420–2424 (2007)

    Article  Google Scholar 

  11. Lysak, P.D., Jenkins, D.M., Capone, D.E., Brown, W.L.: Analytical model of an ultrasonic cross-correlation flow meter, part 2: application. Flow Meas. Instrum. 19(1), 41–46 (2008)

    Article  Google Scholar 

  12. Marioli, D., Narduzzi, C., Offelli, C., Petri, D., Sardini, E., Taroni, A.: Digital time-of-flight measurement for ultrasonic sensors. IEEE Trans. Instrum. Meas. 41(1), 93–97 (1992)

    Article  Google Scholar 

  13. Moazzeni, T., Ma, J., Jiang, Y.: Measurement and calibration of thermal cross-correlation-based flowmeter operating in harsh environment. IEEE Trans. Instrum. Meas. 62(8), 2280–2285 (2013)

    Article  Google Scholar 

  14. Rajita, G., Mandal, N.: Review on transit time ultrasonic flowmeter. In: 2016 2nd International Conference on Control, Instrumentation, Energy & Communication (CIEC), pp. 88–92. IEEE (2016)

    Google Scholar 

  15. Sirazitdinova, E., Pesic, I., Schwehn, P., Song, H., Satzger, M., Weingartner, D., Sattler, M., Deserno, T.M.: Stereo vision for fully automatic volumetric flow measurement in urban drainage structures. In: Videometrics, Range Imaging, and Applications XIV, vol. 10332, p. 103320M. International Society for Optics and Photonics (2017)

    Google Scholar 

  16. Svilainis, L., Lukoseviciute, K., Dumbrava, V., Chaziachmetovas, A.: Subsample interpolation bias error in time of flight estimation by direct correlation in digital domain. Measurement 46(10), 3950–3958 (2013)

    Article  Google Scholar 

  17. Thorn, R., Johansen, G., Hjertaker, B.: Three-phase flow measurement in the petroleum industry. Meas. Sci. Technol. 24(1), 012003 (2012)

    Article  Google Scholar 

  18. Tummers, J.S., Kerr, J.R., O’Brien, P., Kemp, P., Lucas, M.C.: Enhancing the upstream passage of river lamprey at a microhydropower installation using horizontally-mounted studded tiles. Ecol. Eng. 125, 87–97 (2018)

    Article  Google Scholar 

  19. Vogt, M., Gevers, M., Musch, T.: Evaluation of transducer configurations for ultrasound cross-correlation flowmeters. In: 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, pp. 40–44. IEEE (2014)

    Google Scholar 

  20. Wright, S., Nocedal, J.: Numerical optimization. Science 35, 67–68 (1999)

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mathematics, Ege University, Izmir, Turkey

    Nursin Bas Catak

  2. Department of Mathematics and Natural Sciences, GUST, Mubarak Al-Abdullah, Kuwait

    Ali R. Ansari

Authors
  1. Nursin Bas Catak
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  2. Ali R. Ansari
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Corresponding author

Correspondence to Nursin Bas Catak .

Editor information

Editors and Affiliations

  1. Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey

    Tofigh Allahviranloo

  2. Faculty of Engineering and Natural Sciences, Bahçeşehir University, Istanbul, Turkey

    Soheil Salahshour

  3. Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey

    Nafiz Arica

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Catak, N.B., Ansari, A.R. (2021). Time of Flights Estimations of Ultrasonic Signals Based on Numerical Methods. In: Allahviranloo, T., Salahshour, S., Arica, N. (eds) Progress in Intelligent Decision Science. IDS 2020. Advances in Intelligent Systems and Computing, vol 1301. Springer, Cham. https://doi.org/10.1007/978-3-030-66501-2_64

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