Logistic Regression with Wave Preprocessing to Solve Inverse Problem in Industrial Tomography for Technological Process Control

Tomasz Rymarczyk,Edward Kozłowski,Krzysztof Król,Konrad Niderla,Joanna Maria Wyrwisz,Sylwia Skrzypek-Ahmed,Piotr Gołąbek

doi:10.3390/en14238116

Tomasz Rymarczyk, Edward Kozłowski + Show 5 more

Open Access

https://doi.org/10.3390/en14238116

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Abstract

The research presented here concerns the analysis and selection of logistic regression with wave preprocessing to solve the inverse problem in industrial tomography. The presented application includes a specialized device for tomographic measurements and dedicated algorithms for image reconstruction. The subject of the research was a model of a tank filled with tap water and specific inclusions. The research mainly targeted the study of developing and comparing models and methods for data reconstruction and analysis. The application allows choosing the appropriate method of image reconstruction, knowing the specifics of the solution. The novelty of the presented solution is the use of original machine learning algorithms to implement electrical impedance tomography. One of the features of the presented solution was the use of many individually trained subsystems, each of which produces a unique pixel of the final image. The methods were trained on data sets generated by computer simulation and based on actual laboratory measurements. Conductivity values for individual pixels are the result of the reconstruction of vector images within the tested object. By comparing the results of image reconstruction, the most efficient methods were identified.

Highlights

Familiarization with the characteristics of individual tomographic techniques allows for the proper selection of an image reconstruction method
Industrial tomography belongs to electromagnetic field inverse problems
The monitoring system presented is designed to automate, analyze and optimize processes using industrial tomography to analyze without disturbing its interior

Summary

Introduction

Tomography is a method of examining the interior of objects based on measurements taken at the edge of that object. It is a non-invasive method, which can be used to obtain a cross-section of the element—providing 2D images—or spatially—providing 3D images. Mathematical operations and techniques called tomographic reconstruction are used to obtain the image. Different physical phenomena are used depending on the type of object under study. Depending on the specificity of a given tomographic technique, we can observe both advantages and disadvantages in the areas of accuracy, frequency or resolution of reconstructed images. Familiarization with the characteristics of individual tomographic techniques allows for the proper selection of an image reconstruction method.

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