S.V. Prokopchina1, L.S. Zvyagin2

1, 2 Financial University under the Government of the Russian Federation (Moscow, Russia)
1 svprokopchina@fa.ru, 2 lszvyagin@fa.ru

Problem statement. The modern development of information and measurement systems is characterized by the integration of advanced digital technologies with classical measurement and control methods. It is necessary to carry out a systematic analysis of architectural solutions and methodological approaches to the creation of modern measuring systems for automating monitoring of technical facilities. The issues of using machine learning algorithms and neural networks to improve the efficiency of measuring data processing under the influence of interference and non-stationary factors are investigated.

Goal. The analysis of the effectiveness of the digital twin concept in the design and operation of information and measurement systems is carried out. The methods of ensuring the metrological reliability of modern measuring systems are analyzed, taking into account the requirements of standardization and certification/

Results. The approaches to the implementation of automated predictive diagnostic systems based on the analysis of time series and spectral characteristics of measuring signals are investigated. The results of a comparative analysis of various architectural solutions for building distributed measurement networks with the possibility of remote monitoring are presented.

Practical significance. Promising directions for the development of information and measurement technologies in the context of the digital transformation of industry have been identified. Recommendations on the selection of optimal technical solutions for the creation of measuring systems for various purposes are substantiated. The results obtained can be used in the development and modernization of information and measurement systems for energy, transportation and industrial facilities.

Prokopchina S.V., Zvyagin L.S. Current trends and prospects for the development of applied information and measurement systems for solving monitoring and control automation tasks in complex technical complexes. Dynamics of complex systems. 2025. V. 19. № 5. P. 110−125. DOI: 10.18127/j19997493-202505-13 (in Russian).

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