Nonstationary Image Reconstruction in Ultrasonic Transmission Tomography Using Kalman Filter and Dimension Reduction

Liang, Guanghui; Dong, Feng; Kolehmainen, Ville; Vauhkonen, Marko; Ren, Shangjie

doi:10.1109/tim.2020.3031172

Cited by 23 publications

(8 citation statements)

References 30 publications

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“…𝑅 = 𝜎 2 𝑣 = c te (12) c) Estimation of the state of the electric resistance furnace This estimate is constituted by two following step as the following drawing shows in Figure 5. A step in the evolution of the state of the process between 2 sampling times.…”

Section: Algorithm 31 Development Of the Discrete Kalman Filter Algorithmmentioning

confidence: 99%

“…The KSR algorithm generates an ideal estimate of the temperatures for an electric resistance furnace while reducing the uncertainty in temperature prediction. Some contributions cover the operation of the Kalman stochastic reconstructor (KSR) [12]- [23]. For a wide range of situations and for an even larger class, the KSR is the best (optimal) estimate can be divided into two steps.…”

Section: Introductionmentioning

confidence: 99%

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Study of designing regulator for temperature electrical resistance furnace using Kalman stochastic reconstructor

Kada

Kebir²,

Berka³

et al. 2021

IJEECS

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<span>Electric <span>resistance furnaces are the most popular and widely used industrial electro thermal equipment which continues to be the subject of many improvements. The aim of this paper is to control the temperature of electrical furnace for noisy thermocouple sensors. It can be assessed by observing some variables, which are very difficult to observe. Due to limitations, mainly the location of thermal sensors and their noises. In this case, the temperature measurement is trained with centered Gaussian white noise. The problem of accurate temperatures estimation for such sensors is solved using Kalman filter, which is an optimized estimator that provides a computationally efficient way to estimate system state. Thus, variables that are not directly measurable can be reconstructed from the algorithm. Kalman stochastic reconstructor (KSR). We cannot use with fixed parameters to control the temperature. For this reason, this paper comes up with a KSR approach based pole placement (PL) hybrid controller to realize an algorithm for the temperature control electrical furnace. Results based on Matlab simulation show that the improved algorithm has well produced an optimal estimate of the temperature. Evolving over time from noisy measurements. Hybrid algorithm KSR approach based PL give good performance compared to PL controllers.</span></span>

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Section: Algorithm 31 Development Of the Discrete Kalman Filter Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Study of designing regulator for temperature electrical resistance furnace using Kalman stochastic reconstructor

Kada

Kebir²,

Berka³

et al. 2021

IJEECS

View full text Add to dashboard Cite

show abstract

“…The image reconstruction problem in electrical impedance tomography involves taking measurements with a set of sensors and creating a reconstruction based on these measurements [1][2][3][4][5][6][7][8][9][10][11]. It is worth mentioning that many methods can be used to solve optimization problems that are part of a particular system [12][13][14][15][16][17]. It is also worth realising that for image reconstruction it is necessary to accurately model the area that represents the field of view.…”

Section: Introductionmentioning

confidence: 99%

Investigation of flood embankment seepage using logistic regression with ICA

Kozłowski

Król²,

Niderla

et al. 2022

J. Phys.: Conf. Ser.

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This article analyzes the application of logistic regression with the use of ICA to detect leakages and leakages in flood embankments. As a result of the study, a model analysis was carried out where electrical impedance tomography tests were performed for one and for two rows of electrodes. For the results obtained, it was possible to verify the evaluation of the usefulness of the algorithms in the reconstruction of images derived from electrical impedance tomography. The proposed solution is a method that is non-invasive, and thus the embankment does not have to be destroyed for testing. Additionally, it should be emphasised that it is suitable for spatial imaging. The presented solution is a non-invasive method for assessing the structure of embankments, which is well suited for spatial imaging. The implemented algorithm shows promise in image reconstruction.

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“…For this purpose, a model was defined for each finite element. Several different methods were used to solve the optimization problem [1][2][3][4][5][6][7][8][9][10][11]. The presented solutions are based on electrical impedance tomography [12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Logistic regression application into leak identification of embankment in-depth probe

Kozłowski¹,

Król²,

Rymarczyk³

2022

J. Phys.: Conf. Ser.

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The publication presents the results of research on the method of spatial analysis of moisture in objects with the use of deep-sea electrodes. The research consisted in the preparation and development of algorithms as well as models for the analysis and reconstruction of images on the basis of data obtained from impedance electrical tomography. The selected algorithms were used to convert electrical values into conductance. The input is electrical values and the output is image pixels. The pixels represent the conductance. The paper presents the use of PCA method in logistic regression as well as elastic network in logistic regression for leak detection in embankments. In order to be able to perform the research, deep-sea probes were used to collect data.

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Nonstationary Image Reconstruction in Ultrasonic Transmission Tomography Using Kalman Filter and Dimension Reduction

Cited by 23 publications

References 30 publications

Study of designing regulator for temperature electrical resistance furnace using Kalman stochastic reconstructor

Study of designing regulator for temperature electrical resistance furnace using Kalman stochastic reconstructor

Investigation of flood embankment seepage using logistic regression with ICA

Logistic regression application into leak identification of embankment in-depth probe

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