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Gas/Liquid Two-Phase Flow Regime Recognition Based on Adaptive Wavelet-Based Neural Network

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3 Author(s)
Jun Han ; Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin ; Feng Dong ; Yaoyuan Xu

Flow regime recognition of two-phase flow is of great importance in industrial process. In this paper, a new method is brought forward to recognize the gas/liquid two-phase flow regime. The information of the method that provided by electrical resistance tomography (ERT) is the measured data in horizontal pipe. A new adaptive wavelet-based neural network was introduced and it combines the wavelet transformation with neural network theory in this paper. The parameters of the wavelet are adjusted adaptively according to signal's characteristic in the learning process, so the feature of the signal could be extracted to a large extent and the recognition results of flow regime would be better.

Published in:

2008 Fourth International Conference on Natural Computation  (Volume:5 )

Date of Conference:

18-20 Oct. 2008