2021年土木工程院士知名专家系列讲座暨第十二届全国研究生暑期学校——智能建造专题

2021年7月27日08:30-10:00

会议号：740 651 575

密   码：202107

From Structural Health Monitoring to Digital Twin──An Emerging Trend for Infrastructure Advancement

Dr. Zhengyi Wu is Bentley Fellow and director of the Applied Research Group at Bentley Systems Inc. He is managing the applied research projects for advancing infrastructure, including bridges, buildings and water systems around the world. He is currently leading a large research and development project in Smart Water Grid funded by Singapore National Research Foundation under Competitive Research Program and administered by Singapore Public Utility Board, and also conducting the collaborative research on various topics with more than a dozen of leading universities in USA. He has published more than 180 technical papers, and is primary inventor of 20 patents issued by USA patent office. He is Fellow of ASCE Environmental and Water Resource Institute, awardee of ASCE, IWA and AWWA. 

Structural health monitoring (SHM) has long been a research domain and proven to be imperative for critical infrastructure. However, the true benefits of SHM cannot be fully realized without a high-fidelity digital twin. A digital twins can be constructed for above- and underground infrastructure, the key is to augment intelligence for digital twins, so that the stakeholders and engineers can derive actional wisdoms from digital twins, make technically-sound decisions and take cost-effective actions for infrastructure operation and maintenance. This talk will briefly elaborate SHM research and practice, and focus on who digital twin goes mainstream for advancing infrastructure, the needs for adopting digital twin approach for resilient infrastructure, constructing and visualizing high-fidelity digital twins from various data including but not limited images, 3D point cloud and conventional 2D geospatial datasets, coupling infrastructure inspection/ monitoring with the latest machine learning models and physics-based analysis for city-scale resilience, and conducting condition/performance assessment of critical infrastructure such as bridges, buildings and underground utility networks.

2021年7月27日10:10-11:40

会议号：740 651 575

密   码：202107

Robot-assisted Bridge Inspection and Maintenance

Dr. Chen is director of Center for Intelligent Infrastructure, director of INSPIRE University Transportation Center, and associate director of Mid-America Transportation Center. Dr. Chen has authored or co-authored over 400 technical publications. He received the 2019 SHM Person of the Year award, the 2004 Academy of Civil Engineers Faculty Achievement Award, and the NSF CAREER Award, etc. He is a Fellow of ASCE, Structural Engineering Institute (SEI), and the International Society for Structural Health Monitoring of Intelligent Infrastructure (ISHMII). He is a Section Editor of the Intelligent Sensors, Associate Editor of the Journal of Civil Structural Health Monitoring, Associate Editor of Advances in Bridge Engineering, Editorial Board Member of Advances in Structural Engineering, and Vice President of the U.S. Panel on Structural Control and Monitoring.

Recent developments in robotics, measurement science, and the Internet of Things can potentially revolutionize the way and process that civil infrastructures are managed. In this grand yet challenging transition era, automation and informatics are two emerging concepts that will boost a wide range of innovations in civil engineering. In this presentation, new developments and potential applications of nondestructive evaluations, sensing systems, imaging systems, data analytics, and climbing and flying robots will be introduced and reviewed in the context of bridge inspection and maintenance. Sensing and imaging systems and robots can be integrated into the current practice of visual inspection in a systematic framework to transform the current ad-hoc approach to a data-driven management of bridges. Some of the culture and policy challenges in leveraging sensing, imaging, and computer simulation tools for managing existing infrastructures will be discussed.

2021年7月28日08:30-10:00

会议号：740 651 575

密   码：202107

Smart Technology-Enhanced Infrastructure

At Columbia Engineering, Dr. Feng directs the Sensing, Monitoring, and Robotics Technology (SMaRT) Lab. Prior to joining the School, Dr. Feng was Chancellor’s Professor at University of California, Irvine, and founding director of the Center for Advanced Monitoring and Damage Inspection. She is a fellow of ASCE. Dr. Feng has received numerous national and international awards in recognition of her work, including a NSF CAREER Award, the ASCE’s Collingwood Prize and Walter L. Huber Civil Engineering Research Prize, and the Alfred Noble Prize, which is given jointly by the ASCE and other professional societies.

With recent breakthroughs in sensors, computer vision, smartphones, Internet and machine learning, incorporating artificial intelligence into engineering structures is no longer a dream. This talk will first review the state-of-the-art research in exploring advanced technology for structural health monitoring (SHM) to address the challenges facing our society’s aging civil infrastructure.  I will also share the lessons learned from my own research in this field over the last three decades.  Finally, I will discuss opportunities in integrating smart technology for a new paradigm of intelligent maintenance of civil infrastructure systems.

2021年7月28日10:10-11:40

会议号：740 651 575

密   码：202107

土木工程结构智能检测与实时监测技术

张建，美高梅棋牌官网入口教授、博士生导师、副院长。担任智慧建造与运维国家地方工程中心副主任。长期从事结构健康监测研究及工程应用，成果应用于南沙大桥、江苏大剧院等重大工程。先后入选国家级高层次人才、交通部科技创新人才计划、江苏省双创人才计划、江苏省杰青项目、江苏省中青年领军人才，牵头江苏省省优秀科技创新团队。担任CACIE、SCHM等期刊编委、EVACES国际学术会议大会主席、ISHMII国际学会理事。获国家技术发明二等奖、江苏省科学技术一等奖、中国公路学会科学技术一等奖、日内瓦国际发明展金奖、ISHMII国际学会Aftab Mufti奖章、IASCM国际学会Takuji Kobori 奖章。

传统检测技术为保障土木工程结构的安全运营提供了有效手段，但面临依赖人工、效率低、量化难等问题。新型传感、人工智能、云计算等新技术的快速发展为土木工程结构的智能化检测与实时监测提供了独特的发展契机。报告重点介绍两方面工作，一是基于智能空中机器人平台与影像处理的结构病害自动识别、定位和几何信息精准测量的成套方法与装备，解决桥梁高墩、桥塔、桥底等关键区域病害难测的问题；二是基于数字图像、三维激光扫描和微波雷达的系列化结构位移非接触测量技术，解决桥梁关键构件变形和位移难以高效、精准测量的问题。报告还将介绍上述技术应用于苏通大桥等重点工程的检测和评估工作。