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

Konrad Kania, Tomasz Rymarczyk, Mariusz Mazurek, Sylwia Skrzypek-Ahmed, Mirosław Guzik and Piotr Oleszczuk
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Konrad Kania: Faculty of Management, Lublin University of Technology Lublin, 20-618 Lublin, Poland
Tomasz Rymarczyk: Research & Development Center Netrix S.A., 20-704 Lublin, Poland
Mariusz Mazurek: Institute of Philosophy and Sociology, Polish Academy of Science, 00-330 Warsaw, Poland
Sylwia Skrzypek-Ahmed: Faculty of Administration and Social Sciences, University of Economics and Innovation, 20-209 Lublin, Poland
Mirosław Guzik: Faculty of Transport and Computer Science, University of Economics and Innovation, 20-209 Lublin, Poland
Piotr Oleszczuk: Faculty of Management, Lublin University of Technology Lublin, 20-618 Lublin, Poland

Energies, 2021, vol. 14, issue 24, 1-21

Abstract: 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.

Keywords: big data; inverse problem; internet of things; cloud computing; quality of experience; optimisation; ultrasound tomography (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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