Study On Models And Algorithms Of The Electrical Tomography System

As a kind of nondestructive and visible measurement techniques, electrical tomography has found many important applications in both industrial and medical areas, for its low cost and fast response. However, most of the electrical tomography systems are of single modality and using the finite element method in the process of image reconstruction. In order to analyze the measurement mechanism of electrical tomography in depth, the mathematical models of the sensors and associated dual modality image reconstruction algorithms have been investigated systematically in this dissertation.Firstly, mathematical models of calculable sensors are established, in order to calibrate the sensors and perform fast image reconstruction based on the model. The sensors consist of contact-type electrodes and have standard values determined only by the geometric parameters. Dual modality measurement has been performed on a prototype, and the relative errors between measured and theoretical values are less than 1.64% and 2.68% for capacitive mode and conductive mode, respectively. Images have been reconstructed on the prototype using the model based algorithms. The computation complexity of the image reconstruction has been reduced as the finite element method is not used in the image reconstruction. According to Riemann's theorem, the model based algorithms can be generalized to any region enclosed by a Jordan curve.Secondly, two kinds of non-contact type sensors have been constructed, i.e. the senor with a conductive ring and the sensor with an insulative ring. The former is suitable to the flow with a conductive continuous phase. It consists of a conductive ring with electrodes mounted on the ring. The small size electrodes are suitable to improve the distinguishabihty of the voltage measurement and the number of the electrodes. The latter is able to capture the dual modality information with the alternating voltage excitation signal. There exists an insulative ring between the electrode array and the measurement region. As its electrode array have no contact with the measurement region, the sensor has a potential application to non-contact monitoring in the medical area. Based on the models of non-contact sensors, associated spiral type sensor have been designed for void fraction measurement. The global property of the 'soft' field and spatial filtering effect of the spiral type electrodes are utilized to generate a homogeneous sensitivity distribution. Experimental and simulation results validate the linear relationship between the measurements and the void fraction ratios.Thirdly, mathematical models for two-terminal measurement have been established for image reconstruction. Reconstructed images of human body and pipe validate the feasibility of the model based algorithm with the two-terminal measurement. The strategy of the two-terminal measurement simplifies the design of hardware system, reduces the dynamic range of the measurement. And it is useful for smart electrical tomography system. However, different excitation modes can only be used to improve the measurement precision and can not obtain more information.Finally, the linearization in image reconstruction has been analyzed and a robust algorithm based on the model has been proposed for image reconstruction of the human respiration. Results show that the model based algorithms can be generalized using the conformal transformation and can be used for visible monitoring of the human lung activities.The model based methods proposed in this dissertation is not only suitable to visible measurement in two dimensions, but also can be used to simplify the image reconstruction in three dimensions.