Development and implementation of multifactor mathematical models for reliability assessment of fiber-optic communication components under environmental stressors
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1
Department of Electronics, Telecommunications and Space Technologies, Satbayev University, Satbayev str., 22, Almaty, 050013 Republic of Kazakhstan
2
Institute of Mechanics and Mechanical Engineering named after Academician U. A. Dzholdasbekov, Kurmangazy str., 29, Almaty, 050010 Republic of Kazakhstan
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Department of Telecommunication Engineering, Almaty University of Power Engineering & Telecommunications named after G. Daukeev, Baitursynuly str., 126/1, Almaty, 050013 Republic of Kazakhstan
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Department of Mining, Satbayev University, Satbayev str., 22, Almaty, 050013 Republic of Kazakhstan
5
Department of computer technology and cybersecurity, International Information Technology University, Manasa str., 34/1, Almaty, 050040 Republic of Kazakhstan
Corresponding author
Olzhas Suieubayev
Department of Telecommunication Engineering, Almaty University of Power Engineering & Telecommunications named after G. Daukeev, Baitursynuly str., 126/1, Almaty, 050013 Republic of Kazakhstan
Adv. Sci. Technol. Res. J. 2026; 20(3)
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ABSTRACT
This study presents the development and validation of multifactor mathematical models that quantify how combined environmental stressors affect the reliability of fiber-optic communication components, including transceivers and passive modules. The model integrates four key input parameters — temperature (20–50 °C), relative humidity (60–90 %), Еlectromagnetic field (EM field) strength (1-5 V/m), and mechanical vibration (0.1-1.0 g) — to predict the main output quantities: optical power and reliability R(t). The regression and thermo-energetic formulations achieved a mean-squared-error of 0.024 W² and a correlation coefficient of R² = 0.91, while the reliability function estimated R(t) = 94 % after 12 months of average environmental loading. The deviation between modeled and simulated “measured” values did not exceed 1.6 % within the tested ranges, confirming the predictive adequacy of the approach. The models remain applicable for the environmental ranges listed above and can be integrated into real-time monitoring systems for adaptive reliability prediction of fiber-optic infrastructures.