Detail View

Sensitivity map generation in electrical capacitance tomography using mixed normalization models
Citations

WEB OF SCIENCE

Citations

SCOPUS

Metadata Downloads

Title
Sensitivity map generation in electrical capacitance tomography using mixed normalization models
Issued Date
2007-07
Citation
Kim, Yong Song. (2007-07). Sensitivity map generation in electrical capacitance tomography using mixed normalization models. Measurement Science and Technology, 18(7), 2092–2102. doi: 10.1088/0957-0233/18/7/040
Type
Article
Author Keywords
sensitivity mapelectrical capacitance tomographythresholding modeladaptive model
Keywords
Adaptive ModelCapacitanceElectric Field EffectsElectrical Capacitance TomographyFunction EvaluationIMAGE-RECONSTRUCTION ALGORITHMSMathematical ModelsPRINCIPLESSensitivity MapSensorsThresholding ModelTomography
ISSN
0957-0233
Abstract
This work is concerned with the generation of sensitivity maps in electrical capacitance tomography based on the concepts of electrical field centre lines. Electrical capacitance tomography systems are normalized at the upper and lower permittivity values for image reconstruction. Conventional normalization assumes the distribution of materials in parallel and results in normalized capacitance as a linear function of measured capacitance. A recent approach is the usage of a series sensor model which results in normalized capacitance as a nonlinear function of measured capacitance. In this study different forms of normalizations are combined with sensitivity maps based on electrical field centre lines and it is shown that a mix of two normalization models improves the reconstruction performance. © 2007 IOP Publishing Ltd.
URI
http://hdl.handle.net/20.500.11750/56506
DOI
10.1088/0957-0233/18/7/040
Publisher
Institute of Physics and the Physical Society
Show Full Item Record

File Downloads

  • There are no files associated with this item.

공유

qrcode
공유하기

Related Researcher

이성훈
Lee, Seonghun이성훈

Division of Mobility Technology

read more

Total Views & Downloads