Article
Mathematics, Applied
Henrik Garde, Nuutti Hyvonen
Summary: This work presents numerical methods for solving Calderon's problem using series reversions. By reversing the series of the forward map, a family of methods for solving the inverse problem is obtained, and the convergence of these methods is proven. The introduced numerical methods have the same computational complexity as solving the linearized inverse problem.
MATHEMATICS OF COMPUTATION
(2022)
Article
Engineering, Multidisciplinary
Shangjie Ren, Yu Wang, Feng Dong
Summary: A piecewise constant level-set enhanced inclusion boundary reconstruction (PLBR) method is proposed for accurately accessing quantitative information of industrial and biomedical processes in Electrical Impedance Tomography (EIT). The proposed method utilizes a parametric active contour and an augmented least square approach to estimate unknown boundary and conductivity parameters simultaneously. Compared with other methods, the PLBR does not require prior knowledge of the number of target inclusions or conductivity phases, making it applicable in a wider range of scenarios.
Article
Engineering, Electrical & Electronic
Danping Gu, Jiansong Deng, Danny Smyl, Dong Liu, Jiangfeng Du
Summary: This article presents a supershape augmented shape reconstruction algorithm for electrical impedance tomography, which aims at high-quality reconstructions of multiphase conductivity distributions. The algorithm utilizes basic shape primitives expressed through a supershape formula and employs various Boolean operations for automatic topological evolution. Tests using simulations and experimental data demonstrate the algorithm's ability to preserve detailed features of inclusions and provide reliable estimates of unknown conductivity values and interface properties.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Mathematics, Applied
Hongyu Liu, Chun-Hsiang Tsou, Wei Yang
Summary: This paper investigates the recovery of anomalous inhomogeneity shapes in homogeneous conductivity through electric boundary measurements. By relaxing the requirement of corner singularities under a generic technical condition, novel unique recovery results within smooth shapes are derived based on high-curvature conditions.
Article
Mathematics, Applied
Hai-Hua Qin, Hong-Kui Pang, Ji-Chuan Liu
Summary: This paper investigates an inverse scattering problem of reconstructing the shape and impedance of a cavity using one point source and several measurements along a curve inside the cavity. A nonlinear and ill-posed inverse problem is addressed by applying an iterative regularized approach to reconstruct both the boundary and the surface impedance, with injectivity proven for the linearized system at the exact solution. Numerical experiments demonstrate the feasibility and effectiveness of the proposed regularization method.
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS
(2021)
Article
Engineering, Multidisciplinary
Haolong Chen, Bo Yu, Zhanli Liu, Huanlin Zhou
Summary: A non-iterative method based on the boundary element method (BEM) is proposed to estimate unknown boundary geometry shapes and boundary conditions in 2D and 3D isotropic linear elasticity problems. A virtual domain and virtual boundary are introduced to solve the inverse problem. The displacements of the virtual boundary are obtained through the measurement point displacements for shape identification, and the unknown boundary geometry shapes can be estimated by searching the internal point isodisplacement curve. The virtual boundary is overlapped with the real boundary for condition reconstruction, and the unknown boundary tractions can be calculated by the BEM.
ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS
(2023)
Article
Computer Science, Interdisciplinary Applications
Dong Liu, Jiangfeng Du
Summary: This paper addresses the challenge of reconstructing multiphase conductivity distributions using electrical impedance tomography (EIT) by introducing a new reconstruction method utilizing the moving morphable component (MMC) approach and the signed distance-based shape and topology description function (STDF). The MMC approach uses explicit geometric entities controlled by geometric parameters to find optimal inclusion shapes, which is demonstrated through numerical simulation and water tank experiments.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Mathematics, Applied
Isaac Harris
Summary: This paper discusses the use of the Linear Sampling Method for reconstructing impenetrable inclusions from Electrostatic Cauchy data. It proposes a method based on the Dirichlet to Neumann mapping to reconstruct impenetrable sub-regions, as well as a direct method using boundary integral equations to reconstruct the impedance parameter. Numerical reconstructions in two space dimensions are presented.
APPLICABLE ANALYSIS
(2023)
Article
Engineering, Mechanical
Tian Xu, Zhen Wang, Yingda Hu, Shilun Du, Yong Lei
Summary: In this paper, a multiple-data-based direct (MD) method is proposed to solve the inverse problem of estimating the unknown Young's modulus and boundary conditions of an elastic object. It avoids the need for iterative methods. The proposed method applies a global normalized objective function and a global regularization coefficient for energy-like regularization, ensuring the convergence of the unknown displacement boundary conditions. Moreover, a multi-force-position method is proposed to obtain observation data, improving the accuracy of the MD method when the number of experiments is limited. Both numerical and physical experiments confirm that the MD method provides more accurate estimation of Young's modulus and boundary conditions compared to previous single-data-based direct (SD) methods.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2023)
Article
Chemistry, Analytical
Rongqing Chen, Sabine Krueger-Ziolek, Alberto Battistel, Stefan J. Rupitsch, Knut Moeller
Summary: Electrical Impedance Tomography (EIT) is a low-cost imaging method that reconstructs two-dimensional cross-sectional images to visualize impedance changes in the thorax. However, EIT image reconstruction is an ill-posed inverse problem, with issues such as blurring, anatomical alignment, and reconstruction artifacts. This study introduces a patient-specific structural prior mask into the EIT reconstruction process to improve image interpretability. Numerical simulations show that the use of the structural prior mask preserves lung morphology in EIT reconstructions, reduces reconstruction artifacts, and decreases reconstruction error by 25.9% and 17.7% in two EIT algorithms.
Article
Geochemistry & Geophysics
Ahmet Sefer, Ali Yapar
Summary: This paper presents an algorithm for reconstructing locally rough inaccessible surface profiles using scattered field data and the impedance boundary condition. The algorithm solves the surface integral equation iteratively with the data equation to obtain the image of the surface profile. Numerical examples demonstrate the feasibility and effectiveness of the method.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Yu Wang, Feng Dong, Shangjie Ren
Summary: Electrical impedance tomography (EIT) is a promising medical/industrial imaging modality due to its safety, high temporal resolution, and functional imaging characteristics. However, the low spatial resolution caused by the ill-posedness of the inverse problem has hindered its practical applications. This study proposes a flexible image-guided inclusion boundary reconstruction (IGBR) framework for EIT to alleviate this problem. The proposed method shows high applicability to various prior images and achieves high-precision shape reconstruction and conductivity estimation.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Computer Science, Artificial Intelligence
Juan P. Agnelli, Ville Kolehmainen, Matti J. Lassas, Petri Ola, Samuli Siltanen
Summary: The objective of electrical impedance tomography (EIT) is to reconstruct the internal conductivity of a physical body based on current and voltage measurements at the boundary of the body. The proposed method simultaneously reconstructs the conductivity, the contact impedances, and the boundary shape from EIT data, and is illustrated with robust and accurate reconstructions of both conductivity and boundary shape.
SIAM JOURNAL ON IMAGING SCIENCES
(2021)
Article
Mathematics, Applied
Ruchi Guo, Jiahua Jiang
Summary: This study introduces deep direct sampling methods (DDSM) for solving the electrical impedance tomography problem with limited boundary measurements, using deep neural networks to achieve high-quality reconstructions and high robustness to large noise, and employing offline-online decomposition to reduce computational costs and improve efficiency.
SIAM JOURNAL ON SCIENTIFIC COMPUTING
(2021)
Article
Engineering, Electrical & Electronic
Yanyan Shi, Yuehui Wu, Meng Wang, Zuguang Rao, Bin Yang, Feng Fu, Yajun Lou
Summary: This article proposes a novel approach for image reconstruction of conductivity distribution in electrical impedance tomography (EIT). The approach introduces a fidelity term based on L-1 norm to stabilize the problem and enforce sparsity in the solution. It also introduces a hybrid penalty term combining first-order and high-order total variation to preserve sharp profiles and suppress the staircase effect.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Review
Automation & Control Systems
Hongyi Wang, Jiwei Chen, Xinjun Zhu, Limei Song, Feng Dong
Summary: This paper presents an early warning method for compressor valve faults based on multi-parameter signals. By using an improved deep learning network and data processing algorithm, the method achieves parameter prediction and utilizes an information fusion strategy for fault warning. Experimental results demonstrate the effectiveness of this approach in early warning of compressor valve faults.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Saiqiang Liu, Yanbin Xu, Sitong Chen, Qingwei Hu, Feng Dong
Summary: There is currently a lack of a portable and visual real-time monitoring system for early pressure ulcers. A noninvasive imaging system based on electrical impedance tomography (EIT) is proposed to diagnose the healthy condition in tissues. Simulations and physical experiments show that EIT technique has the potential to realize a safer, portable, low-cost, and visual real-time monitoring system for early pressure ulcers.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Wenxiu Hou, Chao Tan, Hao Wu, Feng Dong
Summary: Ultrasound tomography (UT) is proposed as an emerging technique for measuring phase distribution in industrial multiphase flow monitoring. The proposed multimode UT combines ultrasound transmission and reflection modes for measuring stratified phase distribution and sound speed of liquid-solid mixtures in horizontal pipes. The proposed method effectively reconstructs the phase distribution of multiphase media according to numerical investigations and experimental results, with minimum relative error (RE) and maximum correlation coefficient (CC) reaching 0.33 and 0.94, respectively, and an average measurement error (ME) of 3.80% for layer height.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Wei Zhang, Chao Tan, Feng Dong
Summary: In this article, a non-linear and non-convex image reconstruction algorithm based on the homotopy method was proposed to improve the effectiveness and accuracy of classical electrical resistance tomography (ERT) image reconstruction algorithms. Experimental validations and comparisons with other representative algorithms were conducted, and the results showed that the homotopy algorithm provided higher quality and better stability in image reconstruction.
IEEE SENSORS JOURNAL
(2023)
Article
Automation & Control Systems
Wentao Wu, Chao Tan, Shumei Zhang, Feng Dong
Summary: This article proposes a monitoring strategy based on sparse local Fisher discriminant analysis (SLFDA) for accurate identification and real-time monitoring of the flow status of gas-water two-phase flow. The method utilizes multisensor signals and establishes monitoring indexes to analyze the dynamic flow process, enabling fine-scale description and efficient monitoring of flow evolution and instability.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Yixuan Chen, Chao Tan, Feng Dong
Summary: In this study, a multifrequency difference with robust independent component analysis (mfd-RICA) method is proposed to overcome the influence of background head tissues and improve the accuracy of intracranial hemorrhage reconstruction in magnetic induction tomography (MIT). This method extracts the phase shift of hemorrhage using RICA from the measurements based on the multifrequency response model of head tissues in MIT and uses it for conductivity reconstruction. Numerical simulation and phantom experiment results demonstrate that mfd-RICA has high extraction accuracy of the hemorrhage phase shift and can effectively suppress the influence of background tissues to improve the accuracy of hemorrhage reconstruction. Moreover, mfd-RICA is robust to noisy data, facilitating the accurate detection of intracranial hemorrhage. Potentially, this method can enable the detection of acute intracranial hemorrhage with portable MIT devices.
IEEE SENSORS JOURNAL
(2023)
Article
Automation & Control Systems
Hao Liu, Chao Tan, Manuchehr Soleimani, Feng Dong
Summary: In this article, a novel transmission/reflection dual-mode image reconstruction algorithm based on information fusion is proposed. The transmissive attenuation and reflective time-delay information are integrated into an improved Lagrange framework to solve the objective function. The experimental results show that the proposed algorithm outperforms existing image fusion strategies in terms of accuracy and robustness.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Wenxiu Hou, Chao Tan, Hanrui Zhang, Feng Dong
Summary: An ultrasound array strategy with multiple acoustic paths is proposed to improve the measurement accuracy of particle size distribution (PSD). The result shows that the PSD measurements using the ultrasound array method are in agreement with the optical measurement results, and the flow behaviors of the mixing process can be further captured.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Chao Tan, Shiyang Huang, Guanghui Liang, Marco Jose Da Silva, Feng Dong
Summary: In this article, a dual-mode tomography over a wide electrical sensing frequency band based on dual-frequency response is proposed. This technique uses a dual-frequency excitation/probing scheme to measure the capacitance and conductance of the fluid, allowing visualization of the permittivity and conductivity distribution in the same pipe cross section.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Hanrui Zhang, Feng Dong, Chao Tan
Summary: Concentration measurement is crucial for flow assurance and monitoring in industrial processes. The concentration profile is a quantitative parameter to diagnose the states of multiphase flow and has attracted extensive attention from researchers. An ultrasound Doppler technique is utilized for measuring the concentration profile of liquid-solid two-phase flow in a horizontal pipe. A Bayesian inference based on the differential evolution adaptive Metropolis sampling algorithm is proposed for the statistical inversion of the concentration profile. The posterior probability distributions of solid concentration are sampled, and the concentration profile with the maximum a posteriori probability is selected. An experimental platform is constructed for conducting liquid-solid two-phase flow experiments and ultrasound concentration profile measurements. The measured concentration profiles are validated with a maximum mean absolute error of 8.14%.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Chao Tan, Zhixing Zhang, Hao Liu, Rulong Fu, Guide Yang, Feng Dong
Summary: This article presents a novel modular and scalable ultrasonic phased array tomography (UPAT) system for multiphase flow online monitoring. The system includes a master control board and multiple ultrasound transceiver boards, capable of expanding to 128-channel ultrasound transceivers. The system performs well in static imaging experiments, accurately reconstructing the size and location of complex inclusion distribution at a high spatial resolution.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Chao Tan, Haoran Jia, Guanghui Liang, Xuan Wang, Weifei Niu, Feng Dong
Summary: This article introduces a combinable multimodality tomography system based on industrial CPCI bus, which has the advantages of supporting independent work or free combination of different modalities for different measurement requirements. Static experimental results show that the system can coordinate multimodal data acquisition timing and exhibit better performance in terms of acquisition speed, signal-to-noise ratio, and image reconstruction.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Yu Wang, Feng Dong, Shangjie Ren
Summary: Electrical impedance tomography (EIT) is a promising medical/industrial imaging modality due to its safety, high temporal resolution, and functional imaging characteristics. However, the low spatial resolution caused by the ill-posedness of the inverse problem has hindered its practical applications. This study proposes a flexible image-guided inclusion boundary reconstruction (IGBR) framework for EIT to alleviate this problem. The proposed method shows high applicability to various prior images and achieves high-precision shape reconstruction and conductivity estimation.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Shangjie Ren, Jiachen Shi, Ru Guan, Feng Dong
Summary: Electrical impedance tomography (EIT) is a promising technique for monitoring complex dynamics, but its spatial resolution is low due to its ill-posedness and nonlinearity. In order to address this issue, a spatial-temporal regularized learned gradient descent (STLGD) algorithm is proposed, which is implemented using a novel iterative neural network. Experimental results show that STLGD can automatically learn the spatial-temporal correlations among the targets and achieve faster and more accurate conductivity image reconstructions compared to traditional methods.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
