工程结构火灾响应监测与检测研究进展OA
Research progress on monitoring and detection of fire-induced structural responses of engineering structures
火灾严重威胁工程结构安全,常引发构件破坏乃至结构倒塌.目前,仍缺乏覆盖火灾演化与结构损伤的系统性监测与检测体系,实现从灾中实时感知到灾后精准评估是提升结构抗火韧性的关键.为此,围绕结构火灾全过程监测与检测需求,聚焦结构损伤与性能评估,梳理现行结构火灾安全规范,探讨高温下材料性能退化与结构热力响应机理;综述点式传感器、分布式光纤、红外热像等监测与检测设备的研究进展与极端环境适用性,总结新兴人工智能技术在火灾损伤识别与结构响应预测中的应用.研究表明:不同材料体系在高温下呈现差异化失效模式,点式传感器、光纤与声发射等监测与检测技术可支撑高温环境下结构状态感知与损伤动态表征,但检测精度与火场耐久性仍需提升;计算机视觉、人工智能与数字孪生技术可用于结构损伤识别和结构响应预测,但智能算法的泛化能力仍有待加强.
Fire poses a significant threat to the safety of engineering structures,often leading to component failure and even structural collapse.Currently,there is a lack of a systematic monitoring and detection framework that encompasses fire evolution and structural damage.Achieving real-time perception during disasters and precise assessment post-disaster is crucial for enhancing the fire resistance and toughness of structures.In response to whole-process monitoring and detection demands of structural fires,structural damage and performance assessment are emphasized.Current structural fire safety regulations are reviewed,and the degradation of material properties and thermomechanical response mechanisms at high temperatures are examined.Research advances and extreme-environment applicability are summarized for monitoring and detection devices,including point sensors,distributed optical fibers,infrared thermography,and related techniques.The application of emerging artificial intelligence techniques to fire-induced damage identification and structural response prediction is also reviewed.The results indicate that different material systems exhibit distinct failure modes at high temperatures.Monitoring and detection techniques such as point sensors,optical fibers,and acoustic emission can support structural state perception and dynamic damage characterization at high temperatures,whereas detection accuracy and fire-scene durability require improvement.Computer vision,artificial intelligence,and digital twin technologies can be applied to structural damage identification and structural response prediction,but the generalization capability of intelligent algorithms remains to be enhanced.
董一川;姜健;王轶涵;陈伟;叶继红
中国矿业大学 力学与土木工程学院,江苏 徐州 221008中国矿业大学 力学与土木工程学院,江苏 徐州 221008中国矿业大学 力学与土木工程学院,江苏 徐州 221008中国矿业大学 力学与土木工程学院,江苏 徐州 221008中国矿业大学 力学与土木工程学院,江苏 徐州 221008
建筑与水利
工程结构火灾响应监测检测灾后评估人工智能发展趋势
engineering structurefire responsemonitoring and detectionpost-disaster assessmentartificial intelligencedevelopment direction
《建筑结构学报》 2026 (6)
1-25,25
国家自然科学基金项目(52478571).
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