Electrical impedance tomography in 3D flood embankments testing – elastic net approach

Rymarczyk, Tomasz; Kozłowski, Edward; Kłosowski, Grzegorz

doi:10.1177/0142331219857374

Cited by 20 publications

(13 citation statements)

References 29 publications

(25 reference statements)

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“…The traditional approach to modelling an ultrasonic tomograph is to approximate the system behaviour with a model of simple propagation rays between two ultrasonic probes. Publications verify the effectiveness of this solution reliably being able to image the positions of inclusions and the domain of the tomographic system [27][28][29][30][31][32][33][34][35]. Moreover, the effectiveness of such models can be verified by a practical study from measurement data.…”

Section: Innovation Of the Solutionmentioning

confidence: 83%

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Optimisation of Technological Processes by Solving Inverse Problem through Block-Wise-Transform-Reduction Method Using Open Architecture Sensor Platform

et al. 2021

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This paper presents an open architecture for a sensor platform for the processing, collection, and image reconstruction from measurement data. This paper focuses on ultrasound tomography in block-wise-transform-reduction image reconstruction. The advantage of the presented solution, which is part of the project “Next-generation industrial tomography platform for process diagnostics and control”, is the ability to analyze spatial data and process it quickly. The developed solution includes industrial tomography, big data, smart sensors, computational intelligence algorithms, and cloud computing. Along with the measurement platform, we validate the methods that incorporate image compression into the reconstruction process, speeding up computation and simplifying the regularisation of solving the inverse tomography problem. The algorithm is based on discrete transformation. This method uses compression on each block of the image separately. According to the experiments, this solution is much more efficient than deterministic methods. A feature of this method is that it can be directly incorporated into the compression process of the reconstructed image. Thus, the proposed solution allows tomographic sensor-based process control, multidimensional industrial process control, and big data analysis.

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Section: Innovation Of the Solutionmentioning

confidence: 83%

“…Ultrasound tomography, and in particular ultrasound computer tomography (UCT), can be broadly classified into two basic classes: diffraction and classical, and these in turn are divided into reflection and transmission [25][26][27][28][29][30].…”

Section: Ultrasound Transmission Tomographymentioning

confidence: 99%

Optimisation of Technological Processes by Solving Inverse Problem through Block-Wise-Transform-Reduction Method Using Open Architecture Sensor Platform

et al. 2021

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“…where the value c jk is the scaling factor, but d ik is the specific coefficient. Sequence {x t } 1≤tleqm can be expressed in a different form from the level of decomposition j ∈ Z based on Equation (17).…”

Section: Discrete Wavelet Transformation (Dwt)mentioning

confidence: 99%

Application of Electrical Tomography Imaging Using Machine Learning Methods for the Monitoring of Flood Embankments Leaks

et al. 2021

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This paper presents an application for the monitoring of leaks in flood embankments by reconstructing images in electrical tomography using logistic regression machine learning methods with elastic net regularisation, PCA and wave preprocessing. The main advantage of this solution is to obtain a more accurate spatial conductivity distribution inside the studied object. The described method assumes a learning system consisting of multiple equations working in parallel, where each equation creates a single point in the output image. This enables the efficient reconstruction of spatial images. The research focused on preparing, developing, and comparing algorithms and models for data analysis and reconstruction using a proprietary electrical tomography solution. A reliable measurement solution with sensors and machine learning methods makes it possible to analyse damage and leaks, leading to effective information and the eventual prevention of risks. The applied methods enable the improved resolution of the reconstructed images and the possibility to obtain them in real-time, which is their distinguishing feature compared to other methods. The use of electrical tomography in combination with specific methods for image reconstruction allows for an accurate spatial assessment of leaks and damage to dikes.

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“…The novelty presented in this article is the prototype EIT-UST hybrid tomograph dedicated to monitoring industrial tank reactors and pipes. In addition to the concept of connection and the use of tomographic data containing quite different physical quantities (electrical and time), a modified concept of multiple neural networks described in our previous publications was also used [16,45]. The authors' own contribution included the design and development of a tomograph prototype in both the hardware and algorithmic layers.…”

Section: Goal and Noveltiesmentioning

confidence: 99%

Quality Assessment of the Neural Algorithms on the Example of EIT-UST Hybrid Tomography

Kłosowski

Rymarczyk

Cieplak

et al. 2020

Sensors

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The paper presents the results of research on the hybrid industrial tomograph electrical impedance tomography (EIT) and ultrasonic tomography (UST) (EIT-UST), operating on the basis of electrical and ultrasonic data. The emphasis of the research was placed on the algorithmic domain. However, it should be emphasized that all hardware components of the hybrid tomograph, including electronics, sensors and transducers, have been designed and mostly made in the Netrix S.A. laboratory. The test object was a tank filled with water with several dozen percent concentration. As part of the study, the original multiple neural networks system was trained, the characteristic feature of which is the generation of each of the individual pixels of the tomographic image, using an independent artificial neural network (ANN), with the input vector for all ANNs being the same. Despite the same measurement vector, each of the ANNs generates its own independent output value for a given tomogram pixel, because, during training, the networks get their respective weights and biases. During the tests, the results of three tomographic methods were compared: EIT, UST and EIT-UST hybrid. The results confirm that the use of heterogeneous tomographic systems (hybrids) increases the reliability of reconstruction in various measuring cases, which is used to solve quality problems in managing production processes.

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Electrical impedance tomography in 3D flood embankments testing – elastic net approach

Cited by 20 publications

References 29 publications

Optimisation of Technological Processes by Solving Inverse Problem through Block-Wise-Transform-Reduction Method Using Open Architecture Sensor Platform

Optimisation of Technological Processes by Solving Inverse Problem through Block-Wise-Transform-Reduction Method Using Open Architecture Sensor Platform

Application of Electrical Tomography Imaging Using Machine Learning Methods for the Monitoring of Flood Embankments Leaks

Quality Assessment of the Neural Algorithms on the Example of EIT-UST Hybrid Tomography

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