In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for online monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online.

A low-energy low-dose γ-ray computed tomography (CT) system used in the gas-liquid two-phase pipe flow measurement has been studied at Tianjin University in recent years. The γ-ray CT system, having a third-generation X-ray CT scanning configuration, is comprised of one 300mCi Am source and 17 CdZnTe detector units and achieves a spatial image resolution of about 7 mm. It is primarily intended to measure the two-phase pipe flow and provide improvement suggestions for industrial CT system. Recently we improve the design for image reconstruction from incomplete projection to optimize the scanning parameters and reduce the radiation dose. First, tomographic problem from incomplete projections is briefly described. Next, a system structure and a hardware circuit design are listed and explained, especially on time parameter setting of the pulse shaper. And then a detailed system analysis is provided in Section II, mainly focusing on spatial resolution, temporal resolution, system noise, and imaging algorithm. Finally, we carry on necessary static and dynamic experiments in a full scan (360°) and two sets of partial scan reconstruction tests to determine the feasibility of this γ-ray CT system for reconstructing the images from insufficient projections. And based on an A-variable algebraic reconstruction technique method, a specially designed algorithm, we evaluate the system performance and noise level of this CT system working quantitatively and qualitatively. Results of dynamic test indicate that the acceptable results can be acquired using a multi-source γ-ray CT system with the same parameters when the flow rate is less than 0.04 m/s and the imaging speed is slower than 33 frames/s.

Amplitude demodulation is essential in image reconstruction for electrical capacitance tomography (ECT). In this paper, an amplitude demodulation method is proposed based on singular value decomposition (SVD), which can substitute the role of phase-sensitive demodulation in ECT. First, an M × N Hankel matrix is constructed based on a set of discrete samples. Then, SVD operation is performed on the matrix. Finally, the mathematical expression between the sinusoid amplitude and effective singular values is given; i.e., the first two singular values are used to estimate the amplitude information of the acquired signal. The proposed method has the following advantages: (1) since no reference signals are needed, the synchronization between the acquired and reference signals is not necessary; (2) this method can obtain the amplitude information of the acquired signal with a high signal-to-noise ratio (SNR), even in the case of non-integrity period sampling; and (3) SVD itself can also implement the filtering function; thus, no additional low-pass filters are required in the signal conditioning module. The demodulation accuracy and feasibility of the proposed method were verified by numerical simulations and experiments, indicating that it can provide amplitude demodulation with excellent SNR and robust performances.

Electrical Tomography (ET) is an advanced visualization technique, which can reconstruct all targets in an investigated field based on boundary measurements. Since the spatial resolution in the ET process can be greatly affected by the selected similarity norm, different norms may result in different ET time and spatial resolutions. In the tomographic applications nowadays, Bregman divergence (BD) has attracted increasing attention. BDs are a family of generalized similarity norm, and they can measure the similarity/difference between any two targets more accurately. Specifically, the mostly used similarity norm in the ET process (e.g., L2-norm) is only a special case of the BD family. As the key step of applying BD to the ET process, an execution method is proposed in this paper, together with the selection criteria for the optimal norm in the BD family. Simulations and experiments were conducted, and the results show that the use of an optimal BD can effectively improve the spatial resolution of an ET image.

Electrical resistance tomography (ERT) is considered a novel sensing technique for monitoring conductivity distribution. Image reconstruction of ERT is an ill-posed inverse problem. In this paper, an improved regularization reconstruction method is presented to solve this issue. We adopted homotopic mapping to choose the regularization parameter of the iterative Tikhonov algorithm. The standard normal distribution function was used to continuously adjust the regularization parameter. Subsequently, the resultant image vector was deployed as the initial value of the iterative Tikhonov algorithm to improve the image quality. Finally, the improved method was combined with a projection algorithm based on the Krylov subspace, which was also effective in reducing the computational time. Both simulation and experimental results indicated that the new algorithm could improve the real-time performance and imaging quality.