Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Journal Article
Publisher : Biomedical Pharmacology Journal
Source : Biomedical & Pharmacology Journal, Volume 11, Issue 3, p.1471-1477 (2018)
Url : https://www.researchgate.net/publication/327950279_Modeling_and_Calibration_of_Electrical_Capacitanc
Campus : Coimbatore
School : School of Engineering
Department : Electrical and Electronics
Year : 2018
Abstract : Electrical Capacitance Tomography (ECT) is an imaging technique which generates a cross-sectional image representing the internal permittivity distribution based on external capacitance measurements. It possesses the advantages of being non-radioactive, non-intrusive, non-invasive, high imaging speed and low cost over the conventional imaging techniques. Inter-electrode capacitance measurements are done by exciting electrodes placed around the non-conductive dielectric medium cylinder inside which, the material to be imaged is placed. This paper emphasizes on modelling and calibrating an electrical capacitance tomography sensor using ANSYS APDL with medium as air, water and extending the procedure for normal bone and cracked bone. ECT sensor is modelled by mounting 12 electrodes symmetrically outside the cylinder. The cylinder is made up of Polyvinyl Chloride (PVC) which is non-conductive dielectric medium while the electrodes are made up of Copper (Cu) which is conductive. The electrodes are excited in pairs and the potential distribution which is based on permittivity of the medium is analysed using ANSYS and the capacitance between the electrodes were calculated. The entire electrode modelling, calibration and capacitance measurement for the simulated bone model with and without crack is presented in this paper
Cite this Research Publication : S. Selva Kumar and M. Ambika, “Modeling and Calibration of Electrical Capacitance Tomography Sensor for Medical Imaging”, Biomedical & Pharmacology Journal, vol. 11, no. 3, pp. 1471-1477, 2018.