Multichannel Adaptive Systems for Technical Diagnostics

Introduction. In modern industrial production, the role of information and measurement systems for monitoring and diagnostics at all stages of the technological process cannot be underestimated. The increasing complexity of objects leads to a growing volume of measurement information, which reduces the promptness and reliability of monitoring and diagnostics. The conventional approach consists in increasing the computational power, which only postpones the problem. As an alternative, this article proposes changes in the existing algorithmic support by introducing an adaptability mechanism. Adaptive commutation in multichannel technical diagnostic systems with time-division channeling enhances the reliability of monitoring and diagnosing the object under study.

Aim. To develop an algorithmic support for multichannel technical diagnostic systems and, on this basis, to propose a possible version of the structural diagram.

Materials and methods. The study of the adaptation mechanism for multichannel technical diagnostic systems was conducted using the methods of statistical modeling borrowed from queuing theory, with the diagnostic system itself represented as a queuing system.

Results. An algorithmic support and a structural diagram for a multichannel adaptive technical diagnostics system are developed. Mathematical calculations were performed to estimate the multichannel-induced error for this type of systems. The research results can be applied when developing various types of information and measurement systems.

Conclusion. The application of adaptive priority polling in multichannel technical diagnostic systems enhances the reliability and speed of locating faults in complex engineering objects. The studied mathematical framework for assessing the methodological error associated with multichannel operation allows its permissible error margins to be accurately determined.

1. Rubichev N. A. Measuring Information Systems. Moscow, Drofa, 2010. 334 p. (In Russ.)

2. Antonyuk E. M., Varshavskiy I. E., Kolpakova I. S., Minina A. A., Antonyuk P. E. Telemetry System with Adaptive Commutation. Proc. of the IEEE NW Russ. Young Researchers in Electrical and Electronic Engineering Conf., Saint Petersburg, 2–3 Feb. 2016. IEEE, 2016. P. 425–427. doi: 10:1109/ElConRusNW.2016.7448202

3. Antonyuk E. M., Antonyuk P. E., Gvozdev D. S. Adaptive Automatic Control System with Serial Parallel Deviation Analysis. Proc. of the Intern. Scientific and Technical Conf. Samara, Russia, 18–21 Oct. 2022, Samara State University, pp. 15–18.

4. Levenets A. V. Principles of the Development of Promising Methods for Telemetry Data Compression // Bulletin of PNU. 2017, vol. 45, no. 2, pp. 31–38. (In Russ.)

5. Anokhin A. M., Ivkin A. S. Human-Machine Interface for Supporting Cognitive Activity of the AS Operator. Nuclear Measurement and Information Technologies. 2012, no. 1 (41), pp. 57–66. (In Russ.)

6. Antonyuk E. M., Antonyuk P. E., Gvozdev D. S. Technical Diagnostic System with a Multiplicative Maintenance Principle. Proc. of the 2024 XXVII Intern. Conf. on Soft Computing and Measurements (SCM), Saint Petersburg, Russia, 22–24 May 2024. IEEE, 2024, pp. 45–47. doi: 10.1109/SCM62608.2024.10554159

7. Kupriyanova O. V., Levenets A. V. Adaptive Methods of Data Transmission in Information and Measuring Systems. Information Technologies of the 21st Century. 2016, pp. 87–95. (In Russ.)

8. Chye E. U., Bogachev I. V., Levenets A. V. Selection Criteria of the Compression Algorithm in Information-Measuring System. Proc. of the 2nd Intern. Conf. on Industrial Engineering, Applications and Manufacturing (ICIEAM), Chelyabinsk, Russia, 19–20 May 2016. IEEE, 2016, pp. 79–115. doi: 10.1109/ICEAM.2016.7911541

9. Levenets A. V., Chye E. U., Bogachev I. V. Reversible Structural Transformation Methods of Measuring Data Frames as a Means of Increasing the Efficiency of Compression. Proc. of the 2018 Inter Multi-Conf. on Industrial Engineering and Modern Technologies (FarEastCon), Vladivostok, Russia, 3–4 Oct. 2018. IEEE, 2018, pp. 1–6. doi: 10.1109/FastEastCon.2018.8602827

10. Varshavsky I. E. Adaptivnyy kommutator s parallel'nym analizom pogreshnosti approksimatsii [Adaptive Switch with Parallel Approximation Error Analysis]. Pat. RF, no. 2015618795, 2015. (In Russ.)

11. Antonyuk Е. М., Varchavsky I. Е., Antonyuk P. Е., Orlova N. V. Adaptive Transmitting Device of a Telemetering System. Proc. of the IEEE Conf. of Russ. Young Researchers in Electrical and Electronic Engineering (EIConRus), Saint Petersburg, Russia, 28–30 Jan. 2019. IEEE, 2019, pp. 66–68. doi: 10:1109/ElConRus.2019.8656757

12. Kleinrock L. Theory of Mass Service. Moscow, Mashinostroenie, 1979, 432 p. (In Russ.)

13. Sarychev V. V. Telemetering System on the Basis of Intellectual Interfaces. Bulletin of SFedU, technical sciences. 2010, vol. 103, no. 2, pp. 68–73. (In Russ.)

14. Riordan D. Probabilistic Queuing Systems. Moscow, Svyaz, 1966, 184 p. (In Russ.)

15. Wentzel E. S. Probability Theory. Moscow, KNORUS, 2016, 764 p. (In Russ.)

16. Zaezdny A. M. Fundamentals of Calculation in Statistical Radio Engineering. Moscow, Svyaz, 1969, 448 p. (In Russ.)