Spatial imaging with 3D capacitance measurements

Tomographic techniques have been widely accepted as a valuable tool for process control and monitoring. The classic tomographic approach is to reconstruct a 2D image of a process cross section. However, most processes take place in 3D space. Effective imaging in 3D process space can be achieved using 3D image reconstruction in two ways. The first (called 2.5D by the authors) is to use a few independent 2D images and to interpolate them into a 3D image. This method has been widely used in medical applications of tomography for many years already. The second method and the subject of this paper is 'real' three-dimensional reconstruction, where sensors provide three-dimensional measurements and a 3D image is directly obtained during the reconstruction process. The latter method has evolved from classic 2D cross-sectional definition to real and direct 3D imaging. The paper presents the authors' work on a 3D capacitance tomography system including issues such as sensor layout, measurement protocol, data simulation, reconstruction algorithm and 3D visualization.