РУС ENG

FUZZY MODEL OF DIAGNOSTICS OF TECHNOLOGICAL PROCESSES

About

News
Aims and Scope
Founder and Publisher
Editorial board
Licensing terms
Privacy Statement
Plagiarism policy
Publication ethics
Archiving Policy
Subscription


For Authors

Instructions for authors
Reviewing proccess
Copyright Notice
License agreement
Article processing charges


Archive

All issues
Search


Contacts

Contacts


K. B. Fam
Tver State Technical University , Tver.
Research interests: automation of technological processes, artificial intelligence systems

P. M. Murashev
Tver State Technical University , Tver.
Research interests: automation of technological processes, artificial intelligence systems

V. N. Bogatikov.
Tver State Technical University , Tver.
Research interests: automation of technological processes, artificial intelligence systems

UDC 519.4
DOI 10.34757/2413-7383.2023.30.3.007
Language:Russian

Annotation: In this paper, a system for ensuring the safety of the technological process using an algorithm for determining the degree of safety at the current moment is presented. To represent an ordered set of faults, the Hasse diagram construction algorithm was used.

Keywords: diagnostics of technological processes, Hasse diagram, fuzzy equality, fuzzy inclusion, graph search.

References:
1. Yarko E., Chernyshov K. (May 2022). Diagnostic problems in human-machine control systems of nuclear power plants. The 2022 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM) (pp. 563-571). IEEE.
2. Weiqi, W., Yanmei, Z., Shouyi, S., & Guoqiang, X. (2021). Development of a dynamic diagnostics system for mine safety based on cloud computing and Internet of Things technology. Journal of Intelligent and Fuzzy Systems, 40(4), 5837-5844.
3. Zuev V. M., Butov O. A., Ivanova S. B., Nikitina A. A., Ulanov S. I. A method for training a neural network for robot control // Problems of artificial intelligence. 2021. No. 2 (21).
4. Ivanova S. B., Salnikov I. S., Salnikov R. I. Features and results of group computer diagnostics and drug-free therapy of psycho-emotional states of the work collective in an experiment // Problems of artificial intelligence. 2021. No. 1 (20).
5. Perinskaya E. V. Mathematical modeling of the functioning processes of specialized convective type devices // Problems of artificial intelligence. 2022. No. 2 (25).
6. Toichkin N. A., Bogatikov V. N. Algorithm for determining the security center for assessing the state of a technological process // Information technologies in regional development. Apatity, 2005. Vol. V. P. 68–72.
7. Toichkin, N. Designing the architecture of an information system for diagnosing conditions and managing the safety of technological processes. Scientific and technical bulletin of the Volga region Founders: Russian Science LLC, (3), 128-132.
8. Toichkin, Nikolai Alexandrovich. Diagnostics of conditions and management of process safety using a safety index (using the example of an evaporation shop for the production of chlorine and caustic soda). Diss. Tver. state tech. univ., 2006.
9. Pham, K. B. Modeling the process of drying green tea / K. B. Pham, P. M. Murashev, V. N. Bogatikov // Bulletin of Tver State Technical University. Series: Technical Sciences. – 2023. – No. 3(19). – P. 71-83. – DOI 10.46573/2658-5030-2023-3-71-83. – EDN IZQVSF
10. Pham, K. B. Predictive management of the quality index of the green tea drying process / K. B. Pham, P. M. Murashev, V. N. Bogatikov // Bulletin of the Tver State Technical University. Series: Technical Sciences. – 2022. – No. 4(16). – P. 63-76. – DOI 10.46573/2658-5030-2022-4-63-76. – EDN UGDSMK.
11. Sidikov, I. Kh., Mamasadikov, Y., Mamasodikova, N. Yu., & Makhmudov, I. A. (2022). Fuzzy situational model for controlling technological states of petrochemical plants and complexes. Science and Education, 3(9), 202-213.
12. Perinskaya E. V. Mathematical Modeling Of Operation Processes Of Specialized Convective Type Devices // Problems of artificial intelligence. 2022. No. 2 (25).
13. Perinskaya E. V. Application Of The Computational Experiment Method To The Study Of Parameters Of Convective Processes // Problems of artificial intelligence. 2021. No. 3 (22).
14. Popov D. I., Vinogradov D. V. Analysis of search algorithms in state space. Bulletin of the Moscow State University of Printing, (6), 31-33, 2015.
15. Yao, Liu, Jiahao, Li, Zhigang, Zhao, Jinzhu, Guo, Guohong, Li and Xijing, Zhu (2023). Promising technologies for grinding silicon carbide ceramics: a review. Journal of Advanced Manufacturing Science and Technology, 4(1), 2023016-0.
16. Kofman F.. Introduction to the theory of fuzzy sets. – M.: Radio and Communications, 1982.
17. Zadeh L. The concept of a linguistic variable and its application to making approximate decisions. – M.: Mir. 1976.
18. Poreshin P.P., Popov B.N. Discrete mathematics: sets, relations, logic, automata: Textbook - M.: MAI-PRINT Publishing House, 2014.
19. Listopad N. I., Karuk I. A., Haider A. A. Algorithms for finding the shortest path and their modification. Digital Transformation, (1), 48-63, 2016.
20. Satheesh, T., Premkumar, I. J., Saravanan, R., Bhasker, S., Parthiban, A., and Vijayan, V. (October 2020). Increasing speed, quality and safety of processes through low-cost automation - a practical example. In AIP Conference Proceedings (Vol. 2283, No. 1). AIP Publishing House.

Issues: 3(30)'2023
Section: Math modeling
Cite: Fam, K.B. FUZZY MODEL OF DIAGNOSTICS OF TECHNOLOGICAL PROCESSES // K.B. Fam, P.M. Murashev, V.N. Bogatikov // Проблемы искусственного интеллекта. - 2023. № 3 (30). - http://search.rads-doi.org/project/13749/object/201189 doi: 10.34757/2413-7383.2023.30.3.007