In this study, we propose a new sensor structure with driving electrodes and a new excitation mode in electrical capacitance tomography (ECT) to improve: 1) the low sensitivity distribution in the central area caused by low potential distribution in the central area and 2) the nonuniform sensitivity distribution caused by the nonuniform potential distribution. An imaging method based on sensitivity map optimization is derived through electromagnetic field analysis and numerical simulation. In addition, the change rule of the optimal driving voltage is studied when the excitation voltage of the excitation electrodes and the length of the driving electrodes change. The numerical simulation and experimental results show that the imaging method proposed in this article can distinctively alter the potential distribution and sensitivity distribution in the central area by selecting the optimal driving voltage, which brings significant improvement in image reconstruction.

As a fast and non-intrusive measurement and visualization technique, Electrical Capacitance Tomography (ECT) is rapidly expanding its applications in the research on multiphase flow, fluidization, drying, combustion, and so on. However, the marked unevenness of the sensitivity maps sometimes causes unexpected effects in imaging reconstruction, particularly in three-dimension cases. To exploit the positive potential of this phenomenon, the authors proposed an image fusion method using the data from two units of ECT sensors in this study. This method is used in image fusion on the reconstructed images for a planar sensor and a cylindrical sensor. In contrast to the conventional fusion models that use fixed weight factors for two sources of data, our model forges weight functions that are set preference the strength of the sensitivity maps. The new algorithm is implemented by first extracting the characteristic information out of the ECT images using the Latent Low-Rank Representation and then performing a fusion algorithm with linear weight functions in preference to the significance of the sensitivity maps. The simulation results show that the algorithm effectively retains the advantages of the two units of sensors and mutually compensates the weak points of theirs, and significantly improves the reconstruction quality. The fusion image quality by the new method can response the real situation better in different heights. The results imply that the data fusion might to a significant extend amend the weakness of ECT caused by the uneven sensitivity maps.

Electrical capacitance tomography (ECT) is widely used in industrial two-phase flow detection. Non-iterative algorithms have fast imaging speed but low image spatial resolution, while iterative algorithms improve image resolution by increasing the computation time. To increase the image resolution, one can either increase the complexity of the imaging algorithms or increase the observation data according to different imaging principles. ECT technique is an imaging technique based on Green’s reciprocity theorem, which detects scalar, i.e., capacitance. Green’s reciprocity theorem is an energy reciprocity theorem. In recent years, the momentum reciprocity theorem has been proposed. The imaging principle corresponding to the momentum reciprocity theorem detects vector, which is expected to obtain higher resolution permittivity images. A permittivity imaging method is proposed to better recognize the boundary of the object and reduce the complexity of the algorithm. The core of this method is electrical capacitance tomography based on electromagnetic momentum (ECT-EMM). ECT-EMM is an imaging technique based on the electromagnetic momentum reciprocity theorem, which detects vector, i.e., capacitance gradient. We first obtain the capacitance gradient by the electrodes-moving scheme and the object-moving scheme. According to the principle of ECT-EMM, the permittivity gradient is reconstructed. Then, the permittivity distribution is recovered from the permittivity gradient. In this paper, the principle of ECT-EMM is derived, and the object-moving scheme is used. Numerical simulation and experimental demonstration are performed using the Tikhonov regularization algorithm. The reconstructed images and quantitative metrics show that compared to ECT, the proposed method clearly reflects the boundaries of the two-phase flow and performs more stability with noise for certain objects.

With increasing awareness of energy savings and environmental protection in recently years, more emphasis on the monitoring of the intensity distribution in a flame and its stability have been raised in connection with the improvement of combustion efficiency and pollutant control. Albeit there are different opinions, it is generally recognized that Electrical Capacitance Tomography (ECT) measurement is directly related to the ionization of the flame, which in turn is closely related to the intensity of combustion.In this paper, a novel ECT sensor has been designed to withstand high temperatures and a series of experiments based on ECT system have successfully imaged diffusion flame of methane. Also, simulations on three dimensional sensitivity maps are generated to reconstruct images of 3D flame. Experiments and simulation results based on permittivity characteristics of a flame have successfully been used to image the flame, which in turn proves the assumptions raised in the study