Автоматизований моніторинг мостових споруд на основі штучного інтелекту
DOI:
https://doi.org/10.30977/BUL.2219-5548.2025.109.0.81Ключові слова:
мости, моніторинг технічного стану, штучний інтелект, машинне навчання, безруйнівне тестування, згорткові нейронні мережі, детектори об’єктівАнотація
Мостові споруди є критично важливою складовою транспортної інфраструктури, що потребує постійного моніторингу для виявлення дефектів та запобігання аваріям. Традиційні методи візуального огляду та польові випробування поступаються місцем безруйнівним технологіям – георадарному скануванню, інфрачервоній термографії, лазерному скануванню й відеоаналізу – у поєднанні з мережею IoT‑сенсорів. Інтеграція цих даних із алгоритмами штучного інтелекту та машинного навчання дозволяє автоматизувати виявлення аномалій, класифікацію дефектів і прогнозне обслуговування, значно підвищуючи точність і оперативність діагностики. Огляд сучасних підходів відображає використання CNN, R‑CNN, YOLO, MiniRocket та гібридних фізико-цифрових моделей, а також показує ключові виклики: якість і різноманітність даних, інтерпретованість алгоритмів, обчислювальні обмеження в польових умовах і стійкість до перешкод. Пропонуються напрями подальших досліджень для створення прозорих, адаптивних і енергоефективних систем моніторингу мостів.
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