Title :
Fuzzy Recognition for Gas-liquid Two-phase Flow Pattern Based on Image Processing
Author_Institution :
Shaoxing Coll. of Arts & Sci., Shaoxing
fDate :
May 30 2007-June 1 2007
Abstract :
In order to identify the flow pattern automatically and accurately, a new identification method was developed. Flow images were captured by a high speed CCD in a horizontal pipe. The characteristics of bubbles such as area, width and height were obtained using image processing techniques. First, a fuzzy reasoning method was used to identify stratified flow and annular flow. Then a fuzzy neural network was used to identify the flow pattern of bubbly, slug and plug. Levenberg-Marquart optimized algorithm was used to learn the network, and its constringency is rapid. The experimental results show that the fuzzy method can accurately identify the flow patterns in a horizontal pipe.
Keywords :
computational fluid dynamics; fuzzy neural nets; fuzzy reasoning; image processing; stratified flow; two-phase flow; Levenberg-Marquart optimized algorithm; annular flow; fuzzy reasoning method; fuzzy recognition; gas-liquid two-phase flow pattern; high speed CCD; image processing; stratified flow; Charge coupled devices; Digital images; Fluid flow measurement; Fuzzy control; Fuzzy neural networks; Fuzzy reasoning; Image processing; Image recognition; Pattern recognition; Water storage; fuzzy recognition; image processing; neural network; two-phase flow;
Conference_Titel :
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-0818-4
Electronic_ISBN :
978-1-4244-0818-4
DOI :
10.1109/ICCA.2007.4376595