共查询到20条相似文献，搜索用时 15 毫秒
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两相流测量中电容层析成像图像重建的广义逆最小模解与线性反投影和迭代法的比较 总被引：10，自引：2，他引：10
本文根据电容层析成像ECT(ElectricalCapacitanceTomography)线性化了的电容与图像的关系,求出图像向量的广义逆最小模解。以试验数据对广义逆最小模解的图像重建能力进行研究。通过对广义逆最小模解、线性反投影法和迭代法三者的比较,了解了电容—图像线性方程的解不适宜电容层析图像重建的特点、线性反投影处理复杂物体分布图象的局限性,以及迭代法的优越性。同时发现了不加控制的迭代结果向广义逆最小模解结果趋进的现象。 相似文献
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In order to solve the inverse solution for conductivity distribution in electrical impedance tomography, the one-step Gauss–Newton method is usually employed. Major computational time is involved in the calculation of inverse term of the Jacobian matrix and the complexity increases with the number of electrodes and finite elements. Therefore, to reduce the computational time, the inverse term is replaced with a summation term based on the eigenvalue and eigenvector in the inverse solver. In this paper, a fast inversion method using eigenvalue and eigenvector is developed to monitor the conductivity distribution. Therefore, using the proposed method the computation of inverse matrix is avoided resulting in decrease of the on-line computational time. Numerical simulations and experiments have been carried out to evaluate the performance of the proposed method. 相似文献
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An electrical impedance tomography (EIT) system design is proposed for imaging of phase distribution in gas-water two-phase flow from boundary measurement of electrical potentials in response to direct current (DC) injection. DC injection simplifies substantially the system design, but introduces problems due to polarization of injection electrodes. Electrode polarization means charge accumulation on the electrode-water interface causing a drift in the interfacial potential difference. The polarization problems are coped with by using dedicated electrodes for injection and potential measurement, and using a current source unaffected by the polarization of current-carrying electrodes (CCEs). Furthermore, the polarization of CCEs is controlled, to lessen the possible influence on the sensing electrodes (SEs), by using a short (milliseconds in width) pulse for injection with a charge balanced injection strategy. The impact of electrode polarization and the effectiveness of countermeasures introduced in the present design are discussed through comparisons of measured boundary potentials and of images reconstructed for a simple object simulating large bubbles in water. 相似文献
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Electrical resistance tomography (ERT) is a promising technique with which the conductivity distribution in the detected region can be visualized. Mathematically, the reconstruction of conductivity distribution is a seriously ill-posed inverse problem which poses a great challenge for the ERT sensing technique. The regularization method has been found to be an effective approach in coping with the inverse problem. In this work, a novel reconstruction strategy which combines the non-convex regularization method with Landweber method is proposed for the image reconstruction in ERT. At each iteration, the non-convex regularization is used to constrain the conductivity calculated with the Landweber method. A simple and efficient generalized iterated shrinkage algorithm is developed to solve the proposed method. To validate the performance of the proposed method, a series of numerical simulation is conducted and comparative analysis with other methods is performed. From the results, it can be observed that images with high quality are obtained when reconstructing with the proposed method. The impact of noise on the reconstruction is also investigated which shows that the images reconstructed by the proposed method are the least sensitive to the noise. The performance of the proposed method in the image reconstruction is also verified by experimental data. The results demonstrate that the inclusion is accurately reconstructed and the background is clear when the proposed method is adopted for the image reconstruction. 相似文献
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Imaging objects in electrical capacitance tomography (ECT) measurement are often in a dynamic evolution process, and exploiting the spatial–temporal properties of the dynamic reconstruction objects is crucial for the improvement of the reconstruction quality. Based on the multiple measurement vectors, in this paper a robust dynamic reconstruction model that incorporates the ECT measurement information and the dynamic evolution information of a dynamic object, in which a series of dynamic images is cast as a third-order tensor that the first two dimensions are space and the third is time, is proposed. Under the considerations of the two-dimensional spatial structure property of a difference image and the spatial–temporal property of a third-order image tensor, a new objective functional that fuses the ECT measurement information, the dynamic evolution information, the temporal constraint, the spatial constraint, the low rank constraint of a difference image and the low n-rank constraint of a third-order tensor is proposed, where the images are reconstructed by a batching pattern. The split Bregman iteration (SBI) algorithm is developed for solving the proposed objective functional. Numerical simulations are implemented to demonstrate the advantages of the proposed algorithm on improving the reconstruction quality and the robustness. 相似文献
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Process tomography (PT) techniques have been developed rapidly for visualizing the internal behavior of industrial processes, e.g. multi-phase flow measurement. Most of tomography systems employ a single measurement technique, such as computerized tomography (CT), optical tomography (OT), electrical resistance tomography (ERT) or electrical capacitance tomography (ECT). It is now possible to fit two or more tomographic systems to an industrial process. Detailed information from different modalities can be gained by inspection of separate tomographs, and the advantage of the strongest features provided by each unit can be taken. A combined tomogram can be produced of superior quality to any of the separate tomograms. To maximize the information available from the combined tomographic system, data fusion is the better option. In this paper, a dual-mode tomography system based on capacitance sensor and gamma sensor was developed to capture oil–gas two-phase flow. The two modalities can work at the same time. Two fusion methods, namely image fusion method and data fusion method, are proposed. Both simulation and static experiments for oil–gas two-phase flow were conducted. The reconstruction results of different fusion methods and modalities were compared and discussed. 相似文献
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Compared to general room-temperature fluids, the characteristics of cryogenic fluids, as well as the complexity of the cryogenic environment, pose greater challenges for reconstruction algorithms for Electrical Capacitance Tomography (ECT). Based on deep learning, a hybrid model is proposed for cryogenic fluid ECT image reconstruction in this study. The multi-head self-attention mechanism is employed to initially establish the mapping of capacitance to the image, and then an improved U-net-like convolution neural network is presented to perform deep feature extraction and image reconstruction. The ConvNeXt block is adopted for multi-level feature extraction, and a separate downsampling layer is used to replace the pooling layer. A dataset covering a variety of two-phase typical flow patterns and irregular flow patterns is built for training. A capacitance vector and an image of phase distribution are included in each sample. Extensive numerical experiments are carried out on the trained model. The results show that the model can accurately predict phase distribution and produce a clear interface. Finally, the model was successfully applied in cryogenic experiment to obtain the phase distribution image of liquid nitrogen stratified flow. 相似文献
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Capacitively Coupled Electrical Resistance Tomography (CCERT), which is on the basis of Capacitively Coupled Contactless Conductivity Detection (C4D), is a novel electrical tomography technique. As a developing technique, more research work should be undertaken. This work focuses on the study of image reconstruction algorithm of CCERT. Combining Tikhonov regularization principle and Simultaneous Iterative Reconstruction Technique (SIRT), a new hybrid image reconstruction algorithm is proposed. Tikhonov regularization is introduced to obtain the initial reconstructed image. SIRT is used to obtain the final reconstructed image. With a 12-electrode CCERT prototype, image reconstruction experiments are carried out. Experimental results show that the images reconstructed by the proposed image reconstruction algorithm are satisfactory and are in accord with the actual distributions of two-phase flows. The research work also indicates that the proposed image reconstruction algorithm is more suitable for image reconstruction of CCERT, comparing with the conventional image reconstruction algorithms of Electrical Capacitance Tomography (ECT) and Electrical Resistance Tomography (ERT). 相似文献
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An image reconstruction algorithm based on total variation with adaptive mesh refinement for ECT 总被引：2，自引：0，他引：2
In this paper, a robust image reconstruction algorithm for electrical capacitance tomography (ECT) is proposed. The key feature of the algorithm is the use of adaptive mesh refinement based on total variation (TV) in solving the inverse problem. It keeps the edge preserving and scale-dependent properties of total variation regularization, and enhances the distinguishability by using adaptive mesh refinement. This strategy improves the spatial resolution efficiently with less calculation and is less underdetermined than uniform refinement. Simulation and experimental results show that the algorithm performs better than both standard Tikhonov regularization and the conventional total variation method. 相似文献
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Image reconstruction algorithms play an important role in practical applications of electrical capacitance tomography. In the present paper, a combined image reconstruction method is proposed, which takes the results of Landweber algorithm as the constraint condition of Tikhonov algorithm's regularization parameter, calculates the regular parameter, inverts the inverse matrix of sensitivity matrix, and finally obtains the dielectric constant distribution; thus, reconstructed images with improved clarity were obtained. Simulation test are carried out to evaluate and analyze the proposed method from image error, correlation coefficient, image reconstruction time, and anti-noise ability. The results revealed that the Tikhonov regularization algorithm had excellent anti-noise ability; thus, it significantly improved the clarity of reconstructed images and clearly distinguished the multi-phase flow pattern and distribution. 相似文献
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Electrical resistance tomography (ERT) is a promising measurement technique in industrial process imaging. However, image reconstruction in ERT is an ill-posed inverse problem. Regularization methods have been developed to solve the ill-posed inverse problem. Since the penalty term is a form of L2-norm, Tikhonov regularization method guarantees the stability of the solution, but it always makes the image edge oversmoothed. Total variation (TV) regularization method has good ability of preserving image edges. A hybrid regularization method, which combines Tikhonov with TV regularization method, is proposed to get better reconstructed images. The choice of the adaptive weighted parameter between TV and Tikhonov penalty term has been discussed in detail. In the proposed hybrid regularization method, the function of conductivity gradients is used as the adaptive weighted parameter to control automatically the weighting between the penalty terms from TV and Tikhonov regularization. For the model with sharp edges, the proportion of the penalty term from TV regularization is increased to preserve the edges, while for the model with smooth edges, the proportion of penalty term from Tikhonov regularization is increased to make the solution stable and robust to noise. Both simulation and experimental results of Tikhonov, TV and hybrid regularization method are shown respectively, which indicates that the hybrid regularization method can improve the reconstruction quality with sharp edges and is more robust to noise, and it is applicable for models with different edge characteristic. 相似文献
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Practical applications of the electrical capacitance tomography (ECT) rely mainly on the effectiveness of reconstruction algorithms. In this paper the solution of the inverse problem with the focus on the ECT imaging is reformulated to be an optimization problem by introducing a new loss function with regularizes encoding multiple features of solution. An iterative scheme that decomposes a complex optimization problem into several simpler sub-problems is developed to solve the proposed loss function, in which the linearization approximation and the acceleration strategy are introduced to improve numerical performances. Numerical experiments validate the effectiveness of the proposed imaging method in tackling the ECT inverse problem. 相似文献
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基于衍射的计算机层析成像术是建立在Fourier衍射投影定理基础上的.衍射CT图象重构可看作由非均匀频率样点重建信号的问题.提出一种用于反射型衍射CT的图像重构算法,此方法利用反向散射数据进行2D非均匀Fourier反变换.由于直接的非均匀Fourier反变换不易实现,所以采用基于min-max优化准则的非均匀快速Fourier正变换,通过迭代实现非均匀Fourier逆变换的快速有效计算.为了减少迭代次数加快收敛速度,首先用频域插值法得到重构图像的初值,然后根据min-max准则,每经过一次迭代得到重构图像的一个更新版本,重复多次迭代直至得到可接受的重构结果.给出了数值实验结果.与传统重构算法如Gridding方法相比,该算法计算复杂度相当而重构精度较高. 相似文献
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Electrical resistance tomography (ERT) reconstructs the conductivity distribution from the boundary changes of electrical measurements. The inverse problem of ERT is seriously ill-posed where regularization methods are needed to treat this ill-posedness. A proper choice of regularization parameter which controls the degree of smoothing is very important for these regularization methods. Although have been a variety of methods, such as L-curve method, to choose a reasonable parameter for the problem, these methods usually result in a scalar parameter which cannot distinctly express the spatial characteristic of the conductivity distribution. So a spatially adaptive regularization parameter choice method is proposed for regularizing the inverse problem of ERT based on Tikhonov regularization. Since large regularization parameters can stabilize and smoothen the solution, while small regularization parameters can approximate and sharpen the solution, the proposed method adaptively updates the regularization parameters during the iteration process and provides spatially varying parameter for each pixel of the reconstructed image. When the iteration is stopped, large regularization parameters for the smooth background region and small regularization parameters for the object region can be obtained. The method is discussed using simulated data for some typical conductivity distributions, and further applied to the analysis of real measurement data acquiring from the practical system. The results demonstrate that flexible regularization parameter vectors can be achieved for different distributions and the strength of regularization is adaptively provided for different regions in a specific distribution. The adaptive method achieves an efficient and reliable regularization solution and has outstanding performance in noise immunity especially in smooth background regions. 相似文献
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《Measurement》2016
Electrical impedance tomography (EIT) is a non-invasive approach to reconstruct the cross-section impedance image of the body. Many EIT systems and impedance image reconstruction algorithms have been proposed in previous studies. However, most of these EIT systems are bulky to cause the limitation of applications. In this study, a wearable and wireless EIT system is proposed to reconstruct impedance images non-invasively and wirelessly. By microminiaturizing the conventional EIT system, the proposed system can provide the advantages of small volume and wireless transmission to reduce the application limitation of conventional EIT systems. Finally, the phantom experiment is tested to validate the performance of the proposed EIT system. The experimental results show the average BR value of the reconstructed image obtained by the proposed system being 1.3 ± 0.2 and the averaged location error ratio being about 6.27 ± 3.14%. Therefore, the proposed wearable and wireless EIT system can be viewed as a good system prototype and may be applied to more clinical applications in the future. 相似文献
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In this paper, a direct Landweber method is proposed to estimate on-line resistivity distribution of two-phase flows using electrical resistance tomography. The proposed method is formulated such that the iterative Landweber method is modified for on-line computation and the resistivity distribution is estimated directly by multiplying the measured data with a weighting matrix that is computed off-line. Moreover, to improve the reconstruction performance, adaptive step-lengths for the proposed method are computed. Numerical simulations and phantom experiments have been carried out to evaluate the performance of the proposed method. 相似文献