Version 1
: Received: 28 August 2018 / Approved: 29 August 2018 / Online: 29 August 2018 (05:56:49 CEST)
How to cite:
Rymarczyk, T.; Kłosowski, G.; Kozłowski, E.; Tchórzewski, P. Implementation of Smart Tomographic Sensors in Cyber Physical System for Process Analysis in Industry 4.0. Preprints2018, 2018080482. https://doi.org/10.20944/preprints201808.0482.v1
Rymarczyk, T.; Kłosowski, G.; Kozłowski, E.; Tchórzewski, P. Implementation of Smart Tomographic Sensors in Cyber Physical System for Process Analysis in Industry 4.0. Preprints 2018, 2018080482. https://doi.org/10.20944/preprints201808.0482.v1
Rymarczyk, T.; Kłosowski, G.; Kozłowski, E.; Tchórzewski, P. Implementation of Smart Tomographic Sensors in Cyber Physical System for Process Analysis in Industry 4.0. Preprints2018, 2018080482. https://doi.org/10.20944/preprints201808.0482.v1
APA Style
Rymarczyk, T., Kłosowski, G., Kozłowski, E., & Tchórzewski, P. (2018). Implementation of Smart Tomographic Sensors in Cyber Physical System for Process Analysis in Industry 4.0. Preprints. https://doi.org/10.20944/preprints201808.0482.v1
Chicago/Turabian Style
Rymarczyk, T., Edward Kozłowski and Paweł Tchórzewski. 2018 "Implementation of Smart Tomographic Sensors in Cyber Physical System for Process Analysis in Industry 4.0" Preprints. https://doi.org/10.20944/preprints201808.0482.v1
Abstract
The article presents a cyber-physical system for acquiring, processing and reconstructing images from measurement data. The technology was based on process tomography, intelligent measurement sensors, machine learning, Big Data, Cloud Computing, Internet of Things as a solution for Industry 4.0. Industrial tomography enables observation of physical and chemical phenomena without the need of internal penetration and allows real-time monitoring of production processes. The application includes specialized intelligent devices for tomographic measurements and dedicated algorithms for solving the inverse problem. The work focuses mainly on electrical tomography and image reconstruction using deterministic methods and machine learning, the reconstruction results were compared, different measurement models were used. The researches were carried out for synthetic data and laboratory measurements. The main advantage of the proposed system is the possibility of spatial data analysis and their high processing speed. The presented research results show that the process tomography gives the possibility to analyse the processes taking place inside the facility without disturbing the production, analysis and detection of obstacles, defects and various anomalies. Knowing the characteristics of a given solution, the application allows you to choose the appropriate method to reconstruct the image.
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
