Neural networks approach for prediction of gas–liquid two-phase flow pattern based on frequency domain analysis of vortex flowmeter signals

@article{Sun2007NeuralNA,
  title={Neural networks approach for prediction of gas–liquid two-phase flow pattern based on frequency domain analysis of vortex flowmeter signals},
  author={Zhi-qiang Sun and Hongjian Zhang},
  journal={Measurement Science and Technology},
  year={2007},
  volume={19},
  pages={015401}
}
The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas–liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, a three-layer, feed-forward neural network was designed, and adopted inputs all representing the characteristics of the power spectral density distributions of dynamic differential pressure fluctuations were obtained from a vortex flowmeter. The validity of the… 

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