Abstract
A novel scheme to identify flow regime and measure quality in gas-liquid two-phase using differential pressure signal is proposed. Flow regime is identified based on wavelet analysis and back-propagation (BP) neural network. Nine-scale Haar wavelet decomposition is performed on differential pressure signal. The scale energy ratio is extracted as the input of BP network to identify flow regime. Based on the flow regime information, relation between quality and pressure signal is fitted by polynomial. Experiments show that in annular flow, the polynomial fits well.
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