Identification of gas-liquid two-phase flow regime and quality

被引：0
作者：
Sun, T [1 ]
Zhang, HJ [1 ]
Hu, CY [1 ]
机构：
[1] Zhejiang Univ, Natl Key Lab Ind Control Technol, Dept Control Sci & Engn, Hangzhou 310027, Peoples R China
来源：
IMTC 2002: PROCEEDINGS OF THE 19TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1 & 2 | 2002年
关键词：
two-phase flow; flow regime; wavelet analysis; BP neural network; polynomial;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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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页码：1471 / 1474
页数：4
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