Будь ласка, використовуйте цей ідентифікатор, щоб цитувати або посилатися на цей матеріал: http://elartu.tntu.edu.ua/handle/lib/44658
Назва: Methods and Means of Automatic Statistical Assessment of Information Measuring Systems
Автори: Dubynyak, Taras
Dmytrotsa, Lesia
Yavorska, Myroslava
Shostakivska, Nadia
Manziy, Oleksandra
Приналежність: Ternopil Ivan Puluj National Technical University
Lviv Polytechnic National University
Бібліографічний опис: Dubynyak, T., Dmytrotsa, L., Yavorska, M., Shostakivska, N., Manziy, O. Methods and Means of Automatic Statistical Assessment of Information Measuring Systems. 2023. CEUR Workshop Proceedings, 3628, pp. 450-461
Конференція/захід: Proceedings of the 3rd International Workshop on Information Technologies: Theoretical and Applied Problems 2023
Дата публікації: лис-2023
Дата внесення: 26-бер-2024
Видавництво: CEUR (CEUR-WS.org)
Місце видання, проведення: Ternopil, Ukraine, Opole, Poland
Теми: мathematical support
information measuring syste
metrological analysis
measurement uncertainty
error
imprecise value
inadequate knowledge
subjective error
Короткий огляд (реферат): The method of assessing the accuracy of information and measurement systems is considered, using the example of the system of the oil refining industry. In particular, indicators of temperature, pressure and product level sensors in the tank to optimize the process of transmitting information over significant distances. And formation based on measurement of certain conclusions and implementation of controlling influences on the object. A metrological analysis of the created information and measurement complex was carried out based on this concept of uncertainty. The obtained results were compared with the result of calculating the total error of the channel using the entropy coefficient
URI (Уніфікований ідентифікатор ресурсу): http://elartu.tntu.edu.ua/handle/lib/44658
Перелік літератури: [1] V. O. Yatsuk, T. Z. Bubela, M. M. Mykiychuk, E. V. Pokhodylo, Ensuring metrological reliability in dispersed measuring systems, Measuring technique and metrology, t.79, #3, (2018), pp.71-82. [2] Data-Acquisition-Handbook, A Reference For DAQ and Analog & Digital Signal Conditioning, 2012, MA, USA: Measurement Computing Corporation, 2023. URL: http://www.mccdaq.com/pdfs/anpdf/Data-AcquisitionHandbook.pdf. [3] R. Matviiv, Yu. Yatsuk, V. Yatsuk, Development of Portable DC Voltage Calibrators with Additive Offsets Adjusting, Eastern-European Journal of Enterprise Technologies, no. 5/9 (95), 2018, pp. 35– 42. [4] B. Schweber, “How to Select the Right Galvanic Isolation Technology for IoT Sensors”, Digi-Key's North American Editors, 2017. URL: https://www.digikey.com/en/articles/how-select-galvanicisolation- technology-for-iot-sensors. [5] V. Yatsuk, T. Bubela, M. Mykyjchuk, Je. Pokhodylo, “Ensuring metrological reliability in dispersed measuring systems”. Measuring equipment and metrology, vol. 79, no. 3, 2018, pp. 71–82. [6] O.M. Vasilevskyj, O.G. Ignatenko, Normuvannja pokaznykiv nadijnosti tehnichnyh zasobiv: navchalnyj posibnyk, Vinnutsja,VNTU, 2013. [7] Modeling of electromechanical systems. Mathematical modeling of asynchronous electric drive systems: study guide / O. I. Tolochko. - Kyiv, NTUU "KPI", 2016. - 150 s. [8] S.S. Fedin and I.S. Zubretska, Neural network approximation of calibration characteristics of NTCthermistors: monograph. K.: Interservice, 2017, 196 p. [9] Bondar R.P., Podoltsev O.D. Modeljyvannja elektromehanichnyh system. K.:KNYBA, 2012. 391 s. [10] K.V. Ogorodnyk, B.P. Knyzh, P.M. Ratuzhnyj, O.O. Lazarev, Modeljyvannja v electronitsi : navchalnyj posibnyk,Vinnutsja: VNTU, 2017, p.118. [11] S. Yatsyshyn, B. Stadnyk, Cyber-Physical Systems: Metrological Issues, Internat. Barcelona, Spain: Frequency sensor association publishing, 2016. [12] V. Yatsuk, M. Mykyjchuk, Yu. Yatsuk, “Methods and tools of remote calibration of measurement channels of cyberphysical systems”, in Cyber-Physical Systems: technology for data acquisition, Red. A. Melnyk, Lviv, Ukraine: Magnoliya-2006, 2019. [13] ISO 10012:2003 Measurement management systems - Requirements for measurement processes and measuring equipment, 2022. URL: https://www.iso.org/standard/26033.html. [14] V.I. Milykh, O.O. Shavyolkin, Electrical engineering, electromechanics, electronics and microprocessor technology – Kyiv: Caravel, 2015. [15] S.S. Fedin, I.S. Zubretska, and O.O. Polikarpov, Ensuring the accuracy of construction of calibration characteristics of NTC-thermistors based on neural networks with radial basis functions, Metrology and Devices, no. 1(63), pp. 37–46, 2017. [16] Information Technology. Glossary of terms: DSTU ISO/IEC 2382:2017. K.: SE “UkrNDNC”, 2020, 464 p. [17] Ju. Yatsuk, “Test methods for the operational control of the characteristics of electrical measuring instruments”, in Proc. VIII Conf. Modern devices, materials and technologies for nondestructive testing and technical diagnostics of machine-building and oil and gas equipment, Ivano- Frankivsk, Ukraine, 2017. [18] A.G. Soskov, Yu. P. Kolontaevskyi, Industrial electronics. 2nd. Ed, Kyiv: Caravel, 2016. [19] O. M. Vasilevskyi, Standardization of indicators of metrological reliability, Vinnytsia Polytechnic Institute, 2011, pp. 9–13. [20] E.S. Polishchuk, V.M. Vanko, M.M. Dorozhovets, V.O. Yatsuk, and Yu.V. Yatsuk, Measuring transducers (sensors): textbook. Lviv: National Lviv Polytechnic University, 2015, 584 p. [21] M.R. Petryk, A. Khimich, M.M. Petryk, J. Fraissard, Experimental and computer simulation studies of dehydration on microporous adsorbent of natural gas used as motor fuel, 2019. Fuel239, pp. 1324-1330. [22] P. Kryvyi, V. Dzyura, N. Tymoshenko, P. Maruschak, J. Nugaras, O. Prentkovskis, Probability- Statistical Estimation Method of Feed Influence on As-Turned Finish of Steels and Non-Ferrous Metals. Metals 2018, 8, 965. https://doi.org/10/3390/met8110965. [23] S. Lupenko, I. Lytvynenko, A. Sverstiuk, A. Horkunenko, B. Shelestovskyi, Software for statistical processing and modeling of a set of synchronously registered cardio signals of different physical nature. CEUR Workshop Proceedings, 2021, 2864, pp. 194–205. [24] V. Martsenyuk, A. Sverstiuk, A. Klos-Witkowska, A. Horkunenko, S. Rajba, Vector of diagnostic features in the form of decomposition coefficients of statistical estimates using a cyclic random process model of cardiosignal. Proceedings of the 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2019, 1, pp. 298–303. doi: 10.1109/IDAACS.2019.8924398. [25] V. Martsenyuk, A. Sverstiuk, I. Gvozdetska, Using Differential Equations with Time Delay on a Hexagonal Lattice for Modeling Immunosensors. Cybernetics and Systems Analysis, 2019, 55(4), pp. 625–637. doi: 10.1007/s10559-019-00171-2. [26] L. Khvostivska, M. Khvostivskyy, V. Dunetc, I. Dediv Mathematical and Algorithmic Support of Detection Useful Radiosignals in Telecommunication Networks. Proceedings of the 2nd International Workshop on Information Technologies: Theoretical and Applied Problems (ITTAP 2022). Ternopil, Ukraine, November 22-24, 2022. P.314-318. [27] L. Khvostivska, M. Khvostivskyi, I. Dediv, V. Yatskiv, Y. Palaniza Method, Algorithm and Computer Tool for Synphase Detection of Radio Signals in Telecommunication Networks with Noises. Proceedings of the 1st International Workshop on Computer Information Technologies in Industry 4.0 (CITI 2023). CEUR Workshop Proceedings. Ternopil, Ukraine, June 14-16, 2023. P.173-180.
Тип вмісту: Article
Розташовується у зібраннях:Наукові публікації кафедри українознавства і філософії

Файли цього матеріалу:
Файл Опис РозмірФормат 
paper32.pdf874,64 kBAdobe PDFПереглянути/відкрити


Усі матеріали в архіві електронних ресурсів захищені авторським правом, всі права збережені.