An Ill-Conditioned Optimization Method and Relaxation Strategy of Landweber for EMT System Based on TMR

Self Cite

In the electromagnetic tomography (EMT) system, the soft-magnetic shield is employed to avoid the external interference at low frequency. However, the influence of the soft-magnetic shield on the measurement lacks theoretical exploration, and the design of the soft-magnetic shield is arbitrary. To solve this problem, the effect of different thicknesses and locations of the soft-magnetic shield on the measurement is compared by numerical simulation. It is observed that the soft-magnetic shield not only enhances the boundary measurement data and sensitivity but also improves the quality and stability of the reconstructed images. The smaller the distance between the soft-magnetic shield and the pipe, or the bigger the thickness of the soft-magnetic shield, the better the improvement. The physical mechanism of the above results is explicated by the equivalent magnetic circuit analysis method. Based on the above investigation, the optimal structure of the soft-magnetic shield is designed, and it is verified by experiments.by experiments.

Section: Principle and Sensor Structure Of Tmr-emtmentioning

confidence: 99%

Design of soft-magnetic shield in electromagnetic tomography

Liang,

Wang,

et al. 2023

Self Cite

“…The 30 groups of noisy data with the same SNR (45 dB) the experimental system were used for image reconstruction respectively. Landweber algorithm [23] was employed to the reconstruction gray value. In order to achieve the best quality of image reconstruction of the two modalities respectively, the iterative stopping condition is that the relative variation of the two iteration values is less than 0.01 (EMT) and 0.035 (ERT).…”

Section: Dual-modality Sensor Array Optimizationmentioning

confidence: 99%

Design and optimization of electromagnetic tomography and electrical resistance tomography dual-modality sensor

Wang

Liang

et al. 2022

Electromagnetic tomography and electrical resistance tomography (EMT/ERT) dual-modality sensors can combine the advantages of single-modality sensors and detect the distribution of a three-phase medium in a gas-liquid-solid three-phase fluidized bed containing magnetic catalyst. However, the detailed design and optimization of the structure of the EMT/ERT dual-modality sensor arranged in the same cross-section are lacking. In this paper, this problem is solved from the perspective of mutual interference with both EMT and ERT. In numerical simulations, the boundary measurement data and the quality of reconstructed images are compared between single-modality and dual-modality. It is concluded that the EMT has no interference with the ERT, whereas the EMT is interfered by the ERT with the increase of duty ratio. In addition, it is determined that the position of the center of the coil facing the center of the electrodes and the electrode duty ratio of 0.5 are the optimal dual-modality structure. A dual-modality sensor experiment is carried out, and the optimal structure of dual-modality sensor is further validated.

“…Landweber's algorithm produces sharper images and it is based on optimization theory and takes the idea of most rapid descent to obtain the optimal solution [16]. Too large or too small a step size can lead to a significant reduction in the quality and accuracy of the image reconstruction.…”

Section: Introductionmentioning

confidence: 99%

ECT image reconstruction based on sensitive field expansion and optimization

Huang,

Li,

Wang

et al. 2024

Electrical capacitance tomography (ECT) is an efﬁcient method for addressing the issue of two-phase ﬂow monitoring. Most current methods result in low image reconstruction accuracy due to soft ﬁeld issues. This paper propose an ECT image reconstruction method based on sensitive ﬁeld expansion and optimization, which improve reconstruction efﬁciency and accuracy. Firstly, a sensitivity ﬁeld optimization method based on ﬂow pattern identiﬁcation was proposed. The ﬂow pattern recognition determines the ﬂow pattern to which the input signal belongs and selects the sensitive ﬁeld for the corresponding ﬂow pattern. Secondly, a sensitive ﬁeld expansion method based on feature extraction is proposed. The ECT image is modeled as a FRI signal, sampled using an exponential reproducing kernel. Feature information is extracted from the input signal for data fusion, and the optimized sensitive ﬁeld is expanded into a new sensitive ﬁeld distribution matrix by zero-padding and random reorganization. Then, based on optimized and expanded sensitive ﬁelds, a sparse image reconstruction method is proposed. Image reconstruction by constructing comprehensive observation equation to obtain the original permittivity distribution vector of the ECT system using the sparsity of the sensitivity matrix and capacitance signal. Finally, the ECT hardware system and the upper computer measurement and imaging integration software are designed. The experimental results show that the method outperforms other existing algorithms in terms of imaging indexes, has better imaging results.