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Kinematic Models for Non-stationary Elliptic Region Boundaries in Electrical Impedance Tomography
Ijaz, Umer Zeeshan,Kim, Kyung-Youn 제주대학교 공과대학 첨단기술연구소 2006 尖端技術硏究所論文集 Vol.17 No.2
In this study, we propose kinematic models for dynamic electrical impedance tomography (EIT) shape estimation of regions of known resistivities based on extended Kalman filter(EKF). The EIT inverse problem is formulated as a state estimation problem in which the system is modeled with the state equation and the observation equation. We are especially interested in the estimation of shape of air bubbles and conductive liquid in the industrial process pipelines. The proposed kinematic models are tested with computer simulations. From the simulations, we achieve a promising performance of this approach.
Dynamic Estimation in GPS through Covariance Compensation Extended Kalman Filter
Ijaz, Umer Zeeshan,Kim, Kyung-Youn 제주대학교 공과대학 첨단기술연구소 2005 尖端技術硏究所論文集 Vol.16 No.2
This paper presents a covariance compensation extended Kalman filter(CCEKF) based approach to navigation using the Global Positioning System(GPS). The covariance compensation is used to decrease the effect of unexpected measurement and process uncertainties. This paper relies on a detailed modeling of GPS using the data generated with constant velocity through Yuma Almanac.
Directional Algebraic Reconstruction Technique for Electrical Impedance Tomography
김지훈,최봉열,Umer Zeeshan Ijaz,김봉석,김신,Kyung Youn Kim 한국물리학회 2009 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.54 No.4
We assume that the resistance matrix can be found in electrical impedance tomography (EIT) from the assumption of linear dependence between the voltages and the currents. With the help of the resistance matrix and the transfer impedance between the electrodes, a directional algebraic reconstruction technique (DART) is proposed for EIT. The goal is to reconstruct the resistivity distribution by weighting the matrices that are obtained by calculating the orthogonal distance of the underlying mesh elements from the neighboring port resistivity lines. These weighting matrices, which only depend on the topology of the underlying mesh, can be calculated offline and result in a computationally efficient online procedure with a reasonable image reconstruction performance. Simulation results are provided to validate this approach.
Khambampati, Anil Kumar,Ijaz, Umer Zeeshan,Lee, Jeong Seong,Kim, Sin,Kim, Kyung Youn IOP Pub 2010 Measurement Science and Technology Vol.21 No.3
<P>In industrial processes, monitoring of heterogeneous phases is crucial to the safety and operation of the engineering structures. Particularly, the visualization of voids and air bubbles is advantageous. As a result many studies have appeared in the literature that offer varying degrees of functionality. Electrical impedance tomography (EIT) has already been proved to be a hallmark for process monitoring and offers not only the visualization of the resistivity profile for a given flow mixture but is also used for detection of phase boundaries. Iterative image reconstruction algorithms, such as the modified Newton–Raphson (mNR) method, are commonly used as inverse solvers. However, their utility is problematic in a sense that they require the initial solution in close proximity of the ground truth. Furthermore, they also rely on the gradient information of the objective function to be minimized. Therefore, in this paper, we address all these issues by employing a direct search algorithm, namely the Hooke and Jeeves pattern search method, to estimate the phase boundaries that directly minimizes the cost function and does not require the gradient information. It is assumed that the resistivity profile is known a <I>priori</I> and therefore the unknown information will be the size and location of the object. The boundary coefficients are parameterized using truncated Fourier series and are estimated using the relationship between the measured voltages and injected currents. Through extensive simulation and experimental result and by comparison with mNR, we show that the Hooke and Jeeves pattern search method offers a promising prospect for process monitoring.</P>
Kim, Bong Seok,Ijaz, Umer Zeeshan,Kim, Jeong Hoon,Kim, Min Chan,Kim, Sin,Kim, Kyung Youn IOP Pub 2007 Measurement science & technology Vol.18 No.1
<P>In this paper, an effective nonstationary phase boundary estimation scheme in electrical impedance tomography (EIT) is presented based on the interacting multiple model (IMM) algorithm. The inverse problem is treated as a stochastic nonlinear state estimation problem with the nonstationary phase boundary (state) being estimated online with the aid of the IMM algorithm. In the design of the IMM algorithm multiple models with different process noise covariances are incorporated to improve estimation performance in spite of the modelling uncertainty. Computer simulations are provided to illustrate the proposed algorithm.</P>
Khambampati, Anil Kumar,Rashid, Ahmar,Ijaz, Umer Zeeshan,Kim, Sin,Soleimani, Manuchehr,Kim, Kyung Youn The Royal Society 2009 Philosophical transactions. Series A, Mathematical Vol.367 No.1900
<P>The monitoring of solid-fluid suspensions under the influence of gravity is widely used in industrial processes. By considering sedimentation layers with different electrical properties, non-invasive methods such as electrical impedance tomography (EIT) can be used to estimate the settling curves and velocities. In recent EIT studies, the problem of estimating the locations of phase interfaces and phase conductivities has been treated as a nonlinear state estimation problem and the extended Kalman filter (EKF) has been successfully applied. However, the EKF is based on a Gaussian assumption and requires a linearized measurement model. The linearization (or derivation of the Jacobian) is possible when there are no discontinuities in the system. Furthermore, having a complex phase interface representation makes derivation of the Jacobian a tedious task. Therefore, in this paper, we explore the unscented Kalman filter (UKF) as an alternative approach for estimating phase interfaces and conductivities in sedimentation processes. The UKF uses a nonlinear measurement model and is therefore more accurate. In order to justify the proposed approach, extensive numerical experiments have been performed and a comparative analysis with the EKF is provided.</P>
Sensitivity map generation in electrical capacitance tomography using mixed normalization models
Kim, Yong Song,Lee, Seong Hun,Ijaz, Umer Zeeshan,Kim, Kyung Youn,Choi, Bong Yeol IOP Pub 2007 Measurement Science and Technology Vol.18 No.7
<P>This work is concerned with the generation of sensitivity maps in electrical capacitance tomography based on the concepts of electrical field centre lines. Electrical capacitance tomography systems are normalized at the upper and lower permittivity values for image reconstruction. Conventional normalization assumes the distribution of materials in parallel and results in normalized capacitance as a linear function of measured capacitance. A recent approach is the usage of a series sensor model which results in normalized capacitance as a nonlinear function of measured capacitance. In this study different forms of normalizations are combined with sensitivity maps based on electrical field centre lines and it is shown that a mix of two normalization models improves the reconstruction performance.</P>