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Scientific paper ID 2704 : 2025/3
MODELING THROUGH A GRAPH OF THE RELIABILITY BEHAVIOR OF THE COMPONENT SYSTEM “ELECTRICAL CIRCUITS” OF A COMPLEX TECHNICAL OBJECT
Vladimir Iliev Boyadjiev This study examines the modeling of the reliability behavior of complex technical objects using the tools of graph theory. More specifically, the component system “Electrical Circuits” is modeled with a view to embedding its model in the generalized model of the object under consideration. It is generally accepted practice to synthesize partial reliability models. They are built depending on a specific task, the solution of which must be found. Partial reliability models are preferred in reliability modeling, as they have a number of advantages in the process of their creation and use. However, they have limited functionality due to their main drawback - the lack of comprehensiveness of the processes affecting the operational reliability and operational efficiency of technical objects. It is this comprehensiveness that is ensured when creating a comprehensive reliability model of the object. It makes it possible to take into account the mutual influence of the individual factors determining the reliability of the objects. And this makes it possible to carry out highly effective measures to improve reliability indicators. However, creating a generalized reliability model of a complex technical object is an objectively difficult task. This circumstance arises from the significant heterogeneity of the physics of the processes forming reliability. Therefore, their simultaneous inclusion in one model is usually carried out at a purely mathematical level - quite formally. This is done by way of reliability modeling through a set of numerical values of sets of reliability indicators. By building an informal generalized reliability model, this drawback would be overcome.
моделиране надеждност граф електрически вериги.modeling reliability graph electrical circuitsVladimir Iliev Boyadjiev BIBLIOGRAPHY [1] P. Dhavakumar, S. Vengadeswaran, Software defect prediction using graph sample and aggregate-attention network optimized with nomadic people optimizer for enhancing the software reliability, Computer Standards & Interfaces, Volume 95, January 2026, 104033, ISSN: 0920-5489, 2025, Elsevier BV, [2] Liyuan Kong, Chunjie Yang, Siwei Lou, Yaoyao Bao, Xiaoke Huang, Li Chai, A graph-guided network with adaptive evaluation and improvement for disturbed sensors in fault-tolerant soft sensor modeling, Knowledge-Based Systems, Volume 318, 7 June 2025, 113497, ISSN: 0950-7051, 2024, Elsevier BV [3] Xin Wang, Hang Wang, MinJun Peng, Interpretability study of a typical fault diagnosis model for nuclear power plant primary circuit based on a graph neural network, Reliability Engineering & System Safety, Volume 261, September 2025, 111151, ISSN: 0951-8320, 2025, Elsevier Ltd. [4] Xinxin Liang, Zuoxu Wang, Jihong Liu, A survey of large language model-augmented knowledge graphs for advanced complex product design, Journal of Manufacturing Systems, Volume 80, June 2025, Pages 883-901, ISSN: 0278-6125, 2025, The Society of Manufacturing Engineers. Published by Elsevier Ltd. |