Abstract
The measurement of multiphase flow parameters is essential for the online monitoring of industrial production and energy metering. In this paper, a multi-sensor experimental measurement device is designed based on NIR, acoustic emission sensors, and throated Venturi. The measurement information is decomposed using modal decomposition, and the characteristic variables of the gas volume fraction are extracted by flow noise decoupling and light attenuation analysis. A new gas volume fraction model is proposed based on Gradient Boosting Decision Tree (GBDT) through feature-level fusion, and the Mean Absolute Percentage Error (MAPE) of the gas volume fraction prediction models is within 4% for the three flow patterns. A new flow rate model is established based on the Homogeneous and Collins models. Laboratory results indicate that the MAPE of the flow rate model is 1.56%, and 98.61% relative deviations are within ±20% error band. The study provides a new method for online measurement of multiphase fluid motion and a theoretical basis for sensing mechanism and measurement of multiphase flow.
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