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人工智能数字孪生在桥梁管理中不断演变的角色.pdf

上传人: 科*** 编号:713428 2025-06-08 23页 2.89MB

1、The Evolving Role of AI-enabled Digital Twins in Bridge ManagementDr Vahid MousaviCentre for Infrastructure Engineering(CIE)School of Engineering,Design and Built EnvironmentPostdoctoral ResearcherOverviewOverview About SAHM Team Evolution of Digital Twin in Infrastructure Components of a Bridge Dig

2、ital Twin Role of AI in Digital Twin Real-time Data Integration and Analysis Real time Sensor Technology for Digital Twin The Real-time AI-enabled bridge Digital Twin Case Study:Real-time Monitoring SystemSAHM team at Western Sydney University offers specialised engineering consulting and research c

3、apabilities aimed at identifying practical solutions to clients needs.Inspection and Condition assessment Asset digitalisation Structural analysis and health monitoring Heritage preservation Maintenance planning and priority rankingABOUTABOUT SAHMSAHM TEAMTEAM In the past two decades,the deficiencie

4、s related to ageing bridges have become a common problem throughout the world.A large number of bridges are constructed over 50 years ago and are subjected to deficiencies due to overloading,harsh weather and limited maintenance.42%of all bridges are at least 50 years old7%are structurally deficient

5、A large number of bridges were built in early 1950s35%of them are sub-standardMore than 50%of bridges are more than 50 years oldUSAUKAUSThe Challenges of Ageing in Bridge InfrastructureThe Challenges of Ageing in Bridge Infrastructure Traditional inspection on-site inspectors The results of ineffect

6、ive management would be severe:The repair and maintenance of the existing bridges has become the priority to bridge managers.laborioustime-consumingunsafeexpensive Bridge Management based on regular inspections have been proven to be ineffective.Caprigliola bridge collapse in Italy in 2020Mexico Cit

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本文介绍了AI增强的数字孪生技术在桥梁管理中的应用。关键点如下: 1. 西悉尼大学的SAHM团队专注于为桥梁提供工程咨询和研究,解决老化桥梁问题。 2. 全球大量桥梁超50年历史,面临超载、恶劣天气和缺乏维护等问题,桥梁管理面临挑战。 3. 数字孪生技术通过实时监测桥梁的条件、性能和行为,克服了传统桥梁管理方法的局限。 4. AI在数字孪生中的作用包括实时数据分析、预测性维护、增强模拟能力和改善用户体验。 5. 实时传感器技术(如应变计、加速度计等)为数字孪生提供数据支持。 6. 案例研究:Werrington Bridge利用AI模型成功捕捉到桥梁动态行为,并通过模拟异常评估数字孪生框架的效能。 核心数据: - 全球42%的桥梁至少50年历史,7%结构不足。 - 超过50%的桥梁超过50年历史。 - 2019年台湾桥梁坍塌,2020年意大利Caprigliola桥梁坍塌,凸显桥梁管理问题。
"如何利用AI实现桥梁高效管理?" "数字化双生技术如何变革桥梁维护?" "实时监测下,桥梁数字双生的潜力何在?"
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