Optimisation of Technological Processes by Solving Inverse Problem through Block-Wise-Transform-Reduction Method Using Open Architecture Sensor Platform
Artykuł w czasopiśmie
MNiSW
140
Lista 2021
Status: | |
Autorzy: | Kania Konrad, Rymarczyk Tomasz, Mazurek Mariusz, Skrzypek-Ahmed Sylwia, Guzik Mirosław, Oleszczuk Piotr |
Dyscypliny: | |
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Rok wydania: | 2021 |
Wersja dokumentu: | Drukowana | Elektroniczna |
Język: | angielski |
Numer czasopisma: | 24 |
Wolumen/Tom: | 14 |
Numer artykułu: | 8295 |
Strony: | 1 - 21 |
Impact Factor: | 3,252 |
Web of Science® Times Cited: | 8 |
Scopus® Cytowania: | 8 |
Bazy: | Web of Science | Scopus |
Efekt badań statutowych | NIE |
Materiał konferencyjny: | NIE |
Publikacja OA: | TAK |
Licencja: | |
Sposób udostępnienia: | Witryna wydawcy |
Wersja tekstu: | Ostateczna wersja opublikowana |
Czas opublikowania: | W momencie opublikowania |
Data opublikowania w OA: | 9 grudnia 2021 |
Abstrakty: | angielski |
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. |