ENAC Seminar Series by Dr Z. Lai
Event details
| Date | 24.09.2019 |
| Hour | 16:00 › 17:00 |
| Speaker | Dr Zhilu Lai |
| Location | |
| Category | Conferences - Seminars |
16:00 – 17:00 – Dr Zhilu Lai
Postdoctoral Researcher, ETH Zürich, Switzerland
Data-driven Structural Monitoring and Novel Sensing Techniques for Digital Infrastructure
The vastly increasing availability of data types and quantities, emerging sensing technologies and artificial intelligence, are enabling a digitally-enabled view of infrastructure. For treating structures as digital systems efficient methods and tools for data-driven structural identification, monitoring, and automated infrastructure management are of the essence. The use of interconnected sensors and data mining techniques form pivotal blocks for effectuating the establishment of smart buildings and smart cities. In this talk, Dr Lai will discuss how to use advanced sensing techniques, state-of-art data analytics, and statistical learning to convert multi-type sensor data into explainable information, in the form of interpretable and generalizable models, in service of infrastructure maintenance, integrity assessment, and decision making. The talk will cover: (1) a newly proposed parametric modeling technique based on sparse regularization, termed sparse structural system identification; (2) full-field structural monitoring using bio-inspired sensors and event cameras; (3) video-guided hybrid monitoring of infrastructure. Laboratory experiments and real-world case studies are provided for demonstrating the proposed frameworks.
Postdoctoral Researcher, ETH Zürich, Switzerland
Data-driven Structural Monitoring and Novel Sensing Techniques for Digital Infrastructure
The vastly increasing availability of data types and quantities, emerging sensing technologies and artificial intelligence, are enabling a digitally-enabled view of infrastructure. For treating structures as digital systems efficient methods and tools for data-driven structural identification, monitoring, and automated infrastructure management are of the essence. The use of interconnected sensors and data mining techniques form pivotal blocks for effectuating the establishment of smart buildings and smart cities. In this talk, Dr Lai will discuss how to use advanced sensing techniques, state-of-art data analytics, and statistical learning to convert multi-type sensor data into explainable information, in the form of interpretable and generalizable models, in service of infrastructure maintenance, integrity assessment, and decision making. The talk will cover: (1) a newly proposed parametric modeling technique based on sparse regularization, termed sparse structural system identification; (2) full-field structural monitoring using bio-inspired sensors and event cameras; (3) video-guided hybrid monitoring of infrastructure. Laboratory experiments and real-world case studies are provided for demonstrating the proposed frameworks.
Practical information
- General public
- Free
Organizer
- ENAC
Contact
- Cristina Perez