Nonintrusive Distributed Flow Rate Sensing System Based on Flow-Induced Vibrations Detection

Abstract

Noninvasive real-time distributed pipeline monitoring technology is a key factor for the sustainable development of transportation pipelines. In this work, we have proposed and demonstrated a distributed microstructure optical fiber acoustic sensor (MOF-DAS)-based pipeline flow rate sensing system. Such proposed sensing system is based on the detection of flow-induced vibration (FIV) to achieve the flow rate measurement. We have used the Euler-Bernoulli beam theory to build up the FIV-based flow rate sensing model and numerically analyzed the pressures fluctuation at the wall under different flow rates. The simulation results showed that the standard deviation of pressure fluctuation is quadratically proportional to the flow rate. And we have experimentally verified and realized distributed flow rate detection in a pipe loop system built by a 25-m-long pipeline and a laboratory-made MOF-DAS system, which is the first time that the DAS is used for noninvasively pipeline flow rate detection. The experimental results are consistent with the simulated results very well. In the experiment, the flow rate range we measured was from 0 to 3.6 m/s, in which the measuring sensitivity of MOF-DAS at 3.6 m/s was around 0.03998 rad/(m·s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ). Furthermore, the uncertainty analysis of experimental results shows that the measuring uncertainty is decreasing as increasing of flow rate, which is around 13.75% at the flow rate of 0.8 m/s and reduces to less than 1% at the flow rate of 3.6 m/s. Compare with the results measured by the commercial accelerator, the MOF-DAS-based flow rate sensing system has a better and stable flow rate measuring results. Finally, the MOF-DAS-based distributed flow rate detection system has been successfully applied in the field test, which indicated huge engineering application potential, especially in long-distance pipeline networks.