DocumentCode
1284989
Title
Thick-wall electrical capacitance tomography and its application in dense-phase pneumatic conveying under high pressure
Author
Yang, D.Y. ; Zhou, B. ; Xu, C.L. ; Wang, S.M.
Author_Institution
Coll. of Autom. & Electr. Eng., Nanjing Univ. of Technol., Nanjing, China
Volume
5
Issue
5
fYear
2011
fDate
8/1/2011 12:00:00 AM
Firstpage
513
Lastpage
522
Abstract
The thick-wall ECT system applied in high pressure is introduced, and the pipe wall thickness of ECT sensor is 5 mm. To analyse the effect of pipe wall thickness on ECT sensor, radius electrode ratio is defined as the ratio of inner and outer radius of pipeline. ANSYS and Matlab are combined to simulate sensor characteristic. Linear back projection algorithm is adopted to reconstruct the images of stratified flow, core flow and annular flow with different radius electrode ratios. The results of simulation indicate that there is a small image error under high radius electrode ratio, and the images reconstructed from stratified flow are better than those from core flow and annular flow. The independently developed ECT system is applied to identify the flow regime of gas solid flows in horizontal pipeline with 10 mm inner diameter in a pulverised coal dense-phase pneumatic conveying experimental setup. The pressure is up to 4.0 MPa and the solid gas ratio is up to 11.73 kg/kg. The experimental results of eight-electrode ECT with thick pipeline sensor, which is used on the pulverised coal dense-phase pneumatic conveying experimental setup, are given. Finally, the Fluent simulation of concentration distribution at the similar condition is introduced to validate the ECT imaging result.
Keywords
coal; coal gasification; pulverised fuels; stratified flow; ANSYS; ECT sensor; Matlab; annular flow; core flow; gas solid flow; linear back projection algorithm; pipe wall thickness; pulverised coal dense-phase pneumatic conveying; radius electrode ratio; stratified flow; thick-wall ECT system; thick-wall electrical capacitance tomography;
fLanguage
English
Journal_Title
Image Processing, IET
Publisher
iet
ISSN
1751-9659
Type
jour
DOI
10.1049/iet-ipr.2009.0209
Filename
5963792
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