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http://bura.brunel.ac.uk/handle/2438/1792
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DC Field | Value | Language |
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dc.contributor.author | Xie, CG | - |
dc.contributor.author | Huang, SM | - |
dc.contributor.author | Hoyle, BS | - |
dc.contributor.author | Thorn, R | - |
dc.contributor.author | Lenn, C | - |
dc.contributor.author | Snowden, D | - |
dc.contributor.author | Beck, MS | - |
dc.date.accessioned | 2008-03-06T11:49:49Z | - |
dc.date.available | 2008-03-06T11:49:49Z | - |
dc.date.issued | 1992 | - |
dc.identifier.citation | IEE Proceedings G, 139(1): 89 - 98, Feb 1992 | en |
dc.identifier.issn | 0956-3768 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/1792 | - |
dc.description.abstract | A software tool that facilitates the development of image reconstruction algorithms, and the design of optimal capacitance sensors for a capacitance-based 12-electrode tomographic flow imaging system are described. The core of this software tool is the finite element (FE) model of the sensor, which is implemented in OCCAM-2 language and run on the Inmos T800 transputers. Using the system model, the in-depth study of the capacitance sensing fields and the generation of flow model data are made possible, which assists, in a systematic approach, the design of an improved image-reconstruction algorithm. This algorithm is implemented on a network of transputers to achieve a real-time performance. It is found that the selection of the geometric parameters of a 12-electrode sensor has significant effects on the sensitivity distributions of the capacitance fields and on the linearity of the capacitance data. As a consequence, the fidelity of the reconstructed images are affected. Optimal sensor designs can, therefore, be provided, by accommodating these effects | en |
dc.format.extent | 897088 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | IEEE | en |
dc.subject | Computerised tomography; Electric impedance imaging; Electric sensing devices; Finite element analysis; Image sensors | en |
dc.title | Electrical capacitance tomography for flow imaging: System model for development of image reconstruction algorithms and design of primary sensors | en |
dc.type | Research Paper | en |
Appears in Collections: | Business and Management Brunel Business School Research Papers |
Files in This Item:
File | Description | Size | Format | |
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00125122.pdf | 876.06 kB | Adobe PDF | View/Open |
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