OPEN-SCIENCE SPACE ISSUE: CALIBRATION OF MEASURING CHANNELS OF NON-DISMANTLING CYBER-PHYSICAL SYSTEMS

1
Lviv Polytechnic National University
2
Lviv Polytechnic National University
3
Lviv Polytechnic National University, Ukraine
4
Lviv Polytechnic National University, Ukraine
5
Technical University, Ilmenau, Germany
6
Technical University, Ilmenau, Germany

The analysis of the concept of Open-Science Space is carried out. The existence of ways to achieve reproducibility and traceability of research results performed by a group of worldwide situated Cyber-physical system operators/supervisors is shown. Ways to ensure the efficient operation of Cyber-physical systems as complex technological nondemountable objects with high requirements for metrological characteristics have been studied. To develop the scattered cyberphysical systems, the portable stable-in-time code-controlled measures of physical quantities have been studied. They have to be metrologically confirmed in the laboratory before the delivery to the site of the measuring subsystem for its calibration.

[1] Shaping Europe’s digital future. [Online]. Available: https://digital-strategy.ec.europa.eu/en/policies/ cloud-computing

[2] Sang C. Suh, U. John Tanik, John N. Carbone, Abdullah Eroglu, Applied Cyber-Physical Systems, Springer Link, 2014.

[3] Open Science Framework, University of Arizona. [Online]. Available: https://data.library.arizona.edu/datamanagement/ services/ open-science-framework-osf.

[4] J. de la Vera, A. Ruiz, G. Blondelle, Assurance and Certification of Cyber-Physical Systems: The AMASS Open Source Ecosystem, ResearchGate, August 2020, Journal of Systems and Software. 

https://doi.org/10.1016/j.jss.2020.110812

[5] S. Yatsyshyn, B.Stadnyk, Cyber-Physical Systems and Metrology 4.0. Editors, IFSA Publishing, Barcelona, Spain, 2021.

[6] S. Yatsyshyn, B. Stadnyk, Ya. Yanyshyn, “Information Management and IT Innovation in the Measuring Subsystems of Industry 4.0”, in Proc. of the 22nd Int. Conf. on Inf. Techn. for Practice, Oct. 10, 2019, Ostrava, Czech Republic, pp. 105-112, 2019.

[7] Cyton Board. [Online]. Available: https://docs. openbci.com/Cyton/CytonLanding/

[8] P. Ramasamy, Sh. Tharanyaa, J. Palanivelu, A. Sathesan, Certain Applications of LabVIEW in the Field of Electronics and Communication, 2021. 

https://doi.org/10.5772/intechopen.96301

[9] A. Hartland, “The quantum Hall effect and resistance standards”, Metrologia, vol.29, p.175–190, 1992.

https://doi.org/10.1088/0026-1394/29/2/006

[10] R. Benitez, C. Ramirez, J. Vazquez, Sensors calibration for Metrology 4.0, in Proc.of the II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT), Naples, Italy, 4-6 June 2019, pp. 296-299.

https://doi.org/10.1109/METROI4.2019.8792886

[11] R.Taymanov, K.Sapozhnikova, “Metrological selfcheck of sensors”, ResearchGate, Feb. 2011.

[12] B. Jeckelmann, B. Jeannere, “The Quantum Hall Effect as an Electrical Resistance Standard”, Seminaire Poincare, 2, pp.39-51, 2004. http://www.bourbaphy.fr/ jeanneret.pdf.

[13] H. Chen, V. Jungnickel, V. Pohl, C. von Helmolt, “A multicode space-frequency RAKE receiver”, IEEE Xplore, Sept. 2004; Asilomar Conference on Signals, Systems and Computers, 2004, At: Pacific Grove, CA, USA, Vol.1. 

https://doi.org/10.1109/ACSSC.2004.1399219

[14] E. Budylina, A. Danilov, N. Ordinartseva, “Method of calibrating measuring channels of measuring systems under operating conditions”, , in Proc.of the AMCTM-2017.

[15] M. Jurčević, H. Hegeduš, M. Golub, “Generic System for Remote Testing and Calibration of Measuring Instruments: Security Architecture”, Measurement Science Review, vol.10, no.2, p.50-55, 2010.

https://doi.org/10.2478/v10048-010-0012-8

[16] K. Okorn, M. Hannigan, “Improving Air Pollutant Metal Oxide Sensor Quantification Practices through: An Exploration of Sensor Signal Normalization”, Multi-Sensor and Universal Calibration Model Generation, and Physical Factors Such as Co-Location Duration and Sensor Age, Atmosphere, no.12, p.645, 2021. 

https://doi.org/10.3390/atmos12050645

[17] R. Müller, “Calibration and Verification of Remote Sensing Instruments and Observations”, Remote Sensing, iss.6, pp. 5692-5695, 2014.

https://doi.org/10.3390/rs6065692

[18] ISO 10012:2003(en). Measurement management systems — Requirements for measurement processes and measuring equipment, 2003.

[19] R. Sargent, “Validation and verification of simulation models”, IEEE Xplore, in Proc. of 2004 Winter Simulation Conf., 2004. https://ieeexplore.ieee.org/xpl/ conhome/9441/proceeding

[20] K. Sapozhnikova, R. Taymanov, “Sensor Devices with High Metrological Reliability”, ResearchGate, May 23, 2014. https://www.researchgate.net/publication/221917376.

[21] A. Danilov. New trends in calibration of the measuring systems, in Proc. 7th Int. Conf. "Metrology, Inform.-meas. Techn. & Systems", 2020. http://umj.metrology.kharkov.ua/issue/view/11766