Details

Title

Application of electrical capacitance tomography and artificial neural networks to rapid estimation of cylindrical shape parameters of industrial flow structure

Journal title

Archives of Electrical Engineering

Yearbook

2016

Volume

vol. 65

Numer

No 4 December

Publication authors

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences

Date

2016

Identifier

ISSN: 1427-4221 ; eISSN: 2300-2506

References

Ratajewicz (2002), Neural networks method for identification of the objects behind the screen Trans Med Imaging vol no pp, IEEE, 21, 613. ; Marashdeh (2006), Nonlinear Forward Problem Solution for Electrical Capacitance Tomography Using Feed - Forward Neural Network vol no pp, IEEE Sensors Journal, 6, 441, doi.org/10.1109/JSEN.2005.860316 ; Zhang (2014), Application of electrical capacitance tomography in particulate process measurement - A review Technology vol pp, Advanced Powder, 25, 174, doi.org/10.1016/j.apt.2013.12.003 ; Romanowski (2006), Analysis and Interpretation of Hopper Behaviour Using ECT Part Part Charact vol no pp, Syst, 23, 297. ; Mohamad (2001), Direct process estimation from tomographic data using artificial neural systems of Electronic Imaging vol no pp, Journal, 10, 646. ; Lei (2013), An Image Reconstruction Algorithm for Electrical Capacitance Tomography Based on Robust Principle Component Analysis pp, Sensors, 13, 2076, doi.org/10.3390/s130202076 ; Garbaa (2014), Jackowska Neural network approach to ECT inverse problem solving for estimation of gravitational solids flow In Proc of the Federated Conf on Computer Science and Inf Systems vol Warsaw Poland pp, AAIA, 14, 2014. ; Isaksen (1996), A review of reconstruction techniques for capacitance tomography Meas vol pp, Sci Technol, 7, 325. ; Smolik (2010), Accelerated Levenberg Marquardt Method With an Optimal Step Length in Electrical Capacitance Tomography Conf on Imaging Systems and Techniques pp, IEEE Int, 204. ; Wajman (2013), Metrological evaluation of a electrical capacitance tomography measurement system for two - phase flow fraction determination Meas vol no, Sci Technol, 24, 065302.

DOI

10.1515/aee-2016-0046

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