人工智能时代混凝土结构耐久性诊断研究进展OA北大核心CSTPCD
Research progress on durability diagnosis of concrete structures based on artificial intelligence
受服役环境的影响,混凝土结构普遍存在性能劣化严重、耐久性不足等问题.对在役混凝土结构进行诊断,准确识别混凝土结构损伤特征,高效评估其服役寿命,已成为保障混凝土结构服役安全的重大需求.以人工检测、传感器监测为主的诊断方法效率低下、准确性较差,难以满足实际工程结构服役安全科学诊断的要求.人工智能可为各领域研究与应用提供创新驱动力,与混凝土结构耐久性诊断技术深度融合,为混凝土结构全寿命周期的智慧运维提供新的方法.通过分析传统混凝土结构耐久性诊断技术的不足与人工智能技术的优势,从混凝土结构耐久性损伤智能感知、耐久性演化智能预测和耐久性状态智能评估等三个方面总结了人工智能在混凝土结构耐久性诊断中的应用.结果显示:人工智能技术为混凝土耐久性损伤检测与监测提供了新思路,结合传统混凝土材料损伤劣化理论,形成混凝土耐久性劣化进程与服役寿命智能预测方法,建立混凝土结构耐久性智能诊断体系,将是未来结构工程领域的重要发展方向.
Concrete structures are often subjected to serious performance deterioration and reduced durability due to environmental influences.Diagnosis of concrete in service,accurate identification of damage characteristics of concrete structures and efficient evaluation of their service lives are important to ensure the service safety of concrete structures.The diagnosis methods based on manual detection and sensor monitoring are inefficient and inaccurate,and cannot meet the requirements of scientific diagnosis for the service safety of actual engineering structures.Artificial intelligence offers novel impetus for research and application across diverse domains,fostering deep integration with concrete structure durability diagnosis technology and furnishing fresh methodologies for intelligent operation and maintenance of concrete structures throughout their entire lifespan.The shortcomings of traditional concrete structure durability diagnosis technology and the advantages of artificial intelligence technology were discussed,and the applications of artificial intelligence in concrete structure durability diagnosis were summarized from three aspects:intelligent recognition of concrete structure durability damage,intelligent prediction of durability evolution and intelligent evaluation of durability state.The results demonstrate that artificial intelligence technology has introduced innovative approaches to detecting and monitoring concrete durability damage,with integrating conventional concrete material damage degradation theory,creating an intelligent prediction methodology for concrete durability degradation process and service life,and establishing an intelligent diagnostic system for concrete structure durability represent pivotal future directions in the field of structural engineering.
罗大明;李凡;牛荻涛
西安建筑科技大学 土木工程学院,陕西西安 710055||西安建筑科技大学 结构工程与抗震教育部重点实验室,陕西西安 710055
土木建筑
混凝土结构深度学习损伤检测智能诊断寿命预测
concrete structuredeep learningdamage detectionintelligent diagnosislife prediction
《建筑结构学报》 2024 (002)
1-13 / 13
国家自然科学基金项目(52278217),陕西省教育厅青年创新团队建设科研计划项目(21JP059).
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