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

Author

Sun, Tao ; Zhang, Hongjian ; Hu, Chiying

Author_Institution

Dept. of Control Sci. & Eng., Zhejiang Univ., Hangzhou, China

Volume

2

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

1471

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.

Keywords

backpropagation; flow measurement; neural nets; polynomials; two-phase flow; wavelet transforms; Haar wavelet decomposition; annular flow; backpropagation neural network; differential pressure signal; flow regime identification; gas-liquid two-phase flow; polynomial fitting; quality measurement; scale energy ratio; wavelet analysis; Chemical industry; Data acquisition; Fluid flow measurement; Neural networks; Polynomials; Pressure measurement; Signal analysis; Signal processing; Testing; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2002. IMTC/2002. Proceedings of the 19th IEEE

ISSN

1091-5281

Print_ISBN

0-7803-7218-2

Type

conf

DOI

10.1109/IMTC.2002.1007175

Filename

1007175