Intrusive and non-intrusive microflow measurement based on distributed optical fiber acoustic sensing

•Distributed acoustic sensing (DAS) is used for flow monitoring, which overcomes complex networking and limited monitoring range in single-point flow measurement.•An exponential relationship between flow rate and pressure is obtained through theoretical analysis and validated by intrusive and non-in...

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Veröffentlicht in:Measurement : journal of the International Measurement Confederation 2023-03, Vol.210, p.112513, Article 112513
Hauptverfasser: Du, Yuankai, Shang, Ying, Wang, Chen, Yi, Jichao, Sun, Maocheng, Yang, Jian, Zhao, Yanjie, Ni, Jiasheng
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Sprache:eng
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Zusammenfassung:•Distributed acoustic sensing (DAS) is used for flow monitoring, which overcomes complex networking and limited monitoring range in single-point flow measurement.•An exponential relationship between flow rate and pressure is obtained through theoretical analysis and validated by intrusive and non-intrusive simulations.•Through distributed experiments, the intrusive monitoring is verified to have a better degree of fitting up to 0.99432 and uncertainty less than 1%. Distributed optical fiber acoustic sensing has become a research hotspot in the field of microflow monitoring due to its simple structure and wide monitoring range. In this paper, a new method of modal frequency analysis is proposed based on the dynamic pressure of pipeline flow. Theoretical analysis and simulation results demonstrate that the pressure has an exponential relationship with the flow rate. Secondarily, an experimental system of intrusive and non-intrusive flow measuring based on distributed acoustic sensing is designed. With the flow rate range of 0.258–0.349 m/s, experimental result shows that the excellent exponential relationship between dynamic pressure and flow rate can be obtained by using the intrusive monitoring with the frequency band of 450 Hz-550 Hz and the non-intrusive monitoring with the frequency range of 750–850 Hz, respectively. The intrusive method has a better fitting and relative measurement error, with the degree of fitting verified up to 0.99432 and the optimal relative measurement error less than 1%.
ISSN:0263-2241
1873-412X
DOI:10.1016/j.measurement.2023.112513