DocumentCode :
2972179
Title :
Frame by frame wavelet decomposition of electrical capacitance values for real time tomometric applications
Author :
Yan, Ru ; Mylvaganam, Saba
Author_Institution :
Fac. of Technol., Telemark Univ. Coll., Porsgrunn, Norway
fYear :
2011
fDate :
28-31 Oct. 2011
Firstpage :
1851
Lastpage :
1854
Abstract :
Electrical Capacitance Tomometric (ECTm) approach is attractive for measurement and control applications in the process industries, although work in process tomography stretching from the inception years up to now had the main focus on tomograms and their refinements. By using the time series of raw capacitance values C(x,y,t) obtained from Electrical Capacitance Tomographic (ECT) modules, it is shown in this paper how the interface height in a pipe transporting oil and gas can be directly read from wavelet based decomposition and reconstruction of raw capacitances. A combination of wavelet based analysis and neural network can accelerate the measurement process and facilitating the ECTm approach in real time control applications especially in the oil and gas industries and in the process industries in general.
Keywords :
computerised instrumentation; flowmeters; multiphase flow; neural nets; time series; ECT module; ECTm approach; electrical capacitance tomographic module; electrical capacitance tomometric approach; electrical capacitance value; frame by frame wavelet decomposition; gas industry; interface height; measurement process; multiphase flow metering; neural network; oil industry; pipe transporting gas; pipe transporting oil; process tomography stretching; raw capacitance value; time series; wavelet based analysis; Artificial neural networks; Capacitance; Capacitance measurement; Electrodes; Fitting; Permittivity measurement; Tomography; Electrical Capacitance Tomometry (ECTm); interface height; neural network; wavelet decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensors, 2011 IEEE
Conference_Location :
Limerick
ISSN :
1930-0395
Print_ISBN :
978-1-4244-9290-9
Type :
conf
DOI :
10.1109/ICSENS.2011.6127277
Filename :
6127277
Link To Document :
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