10.14489/td.2022.01.pp.026-037

2022, 01 January

DOI: 10.14489/td.2022.01.pp.026-037

Kotelnikov V. V., Akimov D. A., Kozelskaya S. O., Guryanova E. O.
DEVELOPMENT OF SOFTWARE AND METHODS FOR PREDICTING THE SERVICE LIFE OF COMPLEX STRUCTURES BASED ON THE RESULTS OF CHRONOLOGICAL DIAGNOSTICS OF THE TECHNICAL CONDITION AND ARTIFICIAL INTELLIGENCE
(pp. 26-37)

Abstract. The methodology and software for assessing the service life of complex structures uses the methods of intellectual analysis to determine the technical state of the structure, taking into account the current state and the influence of external factors.Experimental studies, using the example of a chimney, confirmed the effectiveness of using the developed software for assessing the service life of a structure based on the results of changes in non-destructive testing data, geometric parameters, the influence of climatic and other factors. The methodology and software for assessing the service life of complex structures uses the methods of intellectual analysis to determine the technical state of the structure, taking into account the current state and the influence of external factors. In the course of the software operation, the probability of a preemergency state is analyzed and relationships are built with the results of predicting the service life of the structure.

Keywords: methodology, software, resource of exploitation, constructions, artificial intelligence, neural networks.

+ - About the Authors Click to collapse

V. V. Kotelnikov (NOCHU DPO “Training Center “Safety in Industry”, Moscow, Russia) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.
D. A. Akimov (Institute of Cybernetics of RTU MIREA, Moscow, Russia) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.
S. O. Kozelskaya (JSC “Central Research Institute of Special Engineering”, Khotkovo, Moscow Region, Russia) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.
E. O. Guryanova (Institute of Cybernetics of RTU MIREA, Moscow, Russia) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.

+ - References Click to collapse

1. Decree of the President of the Russian Federation No. 198 "On the Fundamentals of the State Policy of the Russian Federation in the Field of Industrial Safety for the Period up to 2025 and Beyond". Available at: http://kremlin.ru/acts/bank/43022 (Accessed: 24.08.2021). [in Russian language]
2. Occupational Injury Statistics. Available at: https://www.centrattek.ru/info/statistika-proizvod-travmatizm-po-miru-rossija/ (Accessed: 24.08.2021). [in Russian language]
3. Mahutov N. A., Gadenin M. M., Ivanov V. I. (2021). Scientific and methodological base for technical diagnostics of potentially hazardous industrial facilities. Bezopasnost' truda v promyshlennosti, (6), pp. 7 – 14. [in Russian language]
4. Kozel'skaya S. O. (2021). Improving the operational safety of industrial technical systems made of composite materials by predicting their resource based on new methods of non-destructive testing and deep neural networks. Bezopasnost' truda v promyshlennosti, (4), pp. 7 – 12. [in Russian language]
5. Kozel'skaya S. O., Akimov D. A., Andreev A. S. et al. (2021). Application of deep neural networks based on palliative analysis under conditions of incomplete information of optical thermal and electric nondestructive testing for prediction of the limit resource of operation of construction. Kontrol'. Diagnostika, Vol. 24, (3), pp. 4 – 15. [in Russian language] DOI: 10.14489/td.2021.03.pp.004-015

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