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Electrical capacitance tomography for flow imaging: system model for development of image reconstruction algorithms and design of primary sensors

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7 Author(s)
Xie, C.G. ; Dept. of Electr. Eng. & Electron., Univ. of Manchester Inst. of Sci. & Technol., UK ; Huang, S.M. ; Hoyle, B.S. ; Thorn, R.
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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

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Circuits, Devices and Systems, IEE Proceedings G  (Volume:139 ,  Issue: 1 )