Журналы →  Tsvetnye Metally →  2022 →  №5 →  Назад

Название Application of systematic error detection method to integral parameter measurements in sophisticated production processes and operations
DOI 10.17580/tsm.2022.05.11
Автор Temerbekova B. M.
Информация об авторе

National University of Science and Technology MISiS, Almalyk, Republic of Uzbekistan:

B. M. Temerbekova, Head of the Department of Process and Production Automation, PhD (Technical Sciences), e-mail: misis_temerbekova@mail.ru


This paper uses the Lagrange multiplier method to substantiate the general solution for validity control problem in terms of independently measured parameters of material flows. The paper shows that the efficiency of the above method can be raised if certain process parameters are measured in a number of independent ways by a dispatcher control system. A technique is described to adjust the initial measurement signals in case some channels have redundant information. Such technique is applicable if the values to be adjusted are identified over a period of time that greatly exceeds the dynamic memory of the object or if the dynamic links between certain channels are completely compensated and the execution of static equations of the studied processes is a prerequisite for the values to be adjusted. A method for systematic error detection in application to aggregate integral uncorrelated measurements was used as part of the NavoiAzot dispatcher control system for adjustment of per-shift and per-day performance indicators as calculated by the system. The paper considers the problem of selecting and retrieving valid data on the basis of redundant measurements of material flows and flow constraint equations. The paper describes a solution for the problem of selecting and retrieving valid data on the basis of redundant measurements of material flows and flow constraint equations in application to a complex fertilizer production monitoring system.

Ключевые слова Dispatcher control system, validity control, optimization of instrument maintenance routine, model adjustment, error compensation, sensor signal, validity, redundancy, material flows
Библиографический список

1. Gulyamov S. M., Temerbekova B. M. Construction of the vector of minimum works for the performance of the scheduled tasks of the operational and dispatch management of the technological complex. International Journal of Psychosocial Rehabilitation. 2020. Vol. 24, Iss. 3. pp. 225–231. DOI: 10.37200/IJPR/V24I3/PR200773.
2. Samarov K. L. Linear algebra. Learner’s guide. 2009. 34 p.
3. Attia A. A., Horacek P. Adaptation of genetic algorithms for optimization problem solving. 7th International Conference on Computing MENDEL. 2001. Brno, 2001. pp. 36–41.
4. Ilyin N. I., Lukmanova I. G., Nemchin A. M., Nikeshin S. N. et al. Project management. Ed. by V. D. Shapiro. Saint Petersburg : Dva-Tri, 1996. 610 p.
5. Temerbekova B. M. The problem of ensuring validity of initial measurement data in control and management systems. Chemical Technology. Control and Management. 2010. No. 6. pp. 42–44.
6. Zadeh L. A. New frontiers in fuzzy logic. Proceedings of VI IFSA World Congress, San Paulo, Brazil. 1995.
7. Inkov A. K., Fokeeva L. Kh. Ensuring validity of measurement data in process control systems. Nauchnyi aspekt. 2020. Vol. 17, No. 2. pp. 2216–2218.
8. Bogatenkov S. A., Dadaev V. V., Sikharulidze A. S. Application of automatic measurement systems to monitor the validity of measurement data. Proceedings of the 68th science conference “Science at SUSU”. Chelyabinsk, 5-7 April 2016. pp. 384–389.
9. Barinov V. A., Gamm A. Z., Kucherov Yu. N. et al. Automatic dispatcher control in electric power engineering. Ed. by Yu. N. Rudenko and V. A. Semenova. Moscow : Izdatelstvo MEI, 2000. 648 p.
10. Temerbekova B. M. Ensuring validity of measurement data in control systems: Monograph. Germany. 2015. 176 p.

11. Kartuk Yu. M., Serieznov A. N., Trushin V. A. Robust techniques for enhancing the validity of measurement data and their application in measurement systems of mass strength experiment. Nauchnyi vestnik NGTU. 2016. Vol. 63, No. 2. pp. 90–98.
12. Svistunov B. L. Measuring transducers for parametric sensors using analytical redundancy. Measuring. Monitoring. Management. Control. 2017. No. 2. pp. 94–100.
13. Zade L. The concept of a linguistic variable and its application to making approximate decisions. Moscow : Mir, 1995. 166 p.
14. Gamm A. Z., Kolosok I. N. Use of control equations to detect bad telemetry data for a power grid dispatcher control system. Irkutsk, 1998. 24 p.
15. Temerbekova B. M. A simulation model of a production complex comprising interacting production units in information control systems. Industrial Automatic Control Systems and Controllers. 2020. No. 8. pp. 51–59.
16. Levchenko A. A., Stadnik I. L. Analyzing state identification validity with regard to measurement systems. Proceedings of Odessa Polytechnic University. 2006. Iss. 1 (25). pp. 133–138.
17. Kochneva E. S., Pazderin A. V. Analyzing electric power measurement validity using methods of the state estimation theory. Proceedings of the international youth conference Electric Power Engineering As Viewed by Young People 2014. 2014. Vol. 2. pp. 98–102.
18. Pazderin A. V. Developing a software package to improve the validity of loss calculations and measurement data in electric power monitoring systems. Novoe v rossiyskoy elektroenergetike. 2004. No. 9. pp. 25–34.
19. Kochneva E. S., Pazderin A. V. Use of control equations to improve the validity of measurement data. Power system: Management, Competition, Education. Proceedings of the 3rd international conference. 2008. pp. 395–399.
20. STO 70238424. Electric power monitoring systems. Development. Standards and specifications. Introduced: 01.12.2011. Moscow, 2011.
21. Temerbekova B. M. Operational management of technological complexes based on the evaluation of noise immunity of information and control systems. International Engineering Journal For Research and Development. 2020. Vol. 5, Iss. 4. pp. 1–5.

Language of full-text русский
Полный текст статьи Получить