Summer Course on Structural Health Monitoring 2025 (3rd Edition)

5 ECTS | July 14-18, 2025, in person (30h) | 15h remotely | MSc and PhD Students

We are happy to announce the 3rd Edition of the Summer Course on Structural Health Monitoring. The in-person sessions will take place in Lisbon from July 14 to 18, 2025. 

This blended intensive summer course, funded by the Erasmus+ Program, focuses on structural health monitoring (SHM), with 15 hours of remote sessions and 30 hours of in-person sessions. The main goal of this summer course is to introduce the concept of SHM applied to bridges and special civil structures to MSc and PhD students from several European institutions.

The SHM is posed in the context of a statistical pattern recognition paradigm, rooted in the artificial intelligence field to support the damage identification and risk-informed integrity management. Machine learning algorithms are essential to perform damage identification, by learning (or modeling) the structural behavior from the experience (past data), following the same principle of the human brain. 

In order to balance the general concept and the applicability of SHM, this course has been designed to allow students to gain a basic knowledge of SHM with hands-on experiences to demonstrate how SHM can be used for assessing the condition of structural systems, along with the lectures to give some insight into the theory and application examples.

Keywords

Structural Health Monitoring, Bridges, Wind Turbines, Machine Learning, Finite Element Modeling, Digital Twins, Risk, Resilience, Value of Information, Climate Change

Most relevant upgrades since last edition

For the 3rd edition, we are adding two new instructors (Michael Havbro Faber and Luís Oliveira Santos), two new invited instructors (Semih Gonen and Luca Pèla), and more SHM in Action!

Funding source

Erasmus+ Program through Blended Intensive Program (BIP), Student Mobility of Education (SME), and Staff Mobility for Teaching (SMT). The BIP covers expenses related to the course organization. SMT and SME cover expenses related to traveling and housing of students in Lisbon.

Which are the host and partners institutions?

Lusófona University is host and responsible for the organization and funding of the course through BIP. Each partner institution is responsible to find students and staff members through SME and SMT (this funding must be coordinated with the international office of each partner institution).

Who can participate?

MSc and PhD students from countries participating in the Erasmus+ Program who are interested in speeding up the learning process of SHM posed in the context of a statistical pattern recognition paradigm.

Registration

The registration is closed. However, if you are interested in participate just send an email to Este endereço de email está protegido contra piratas. Necessita ter o JavaScript autorizado para o visualizar..

Course material

PowerPoints, books, and research articles: all course materials are available on a virtual drive. Students are encoureged to bring their own laptops.

Student evaluation

The evaluation includes three main components: individual homework, a project report and presentation, and individual assessment. Small groups of four, five, or six students are formed to design an SHM system or a damage identification strategy for laboratory or real-world structures. Each group is assigned a supervisor for guidance.  Each group's outcome must be documented in a report and defended in an oral examination, conducted publicly in the form of a seminar. Students are graded, and the grades will be awarded according to the university’s Education and Examination Regulations.

Remote lectures

1. Introduction to SHM
2. Statistical pattern recognition paradigm
3. Data-based modeling
4. Hybrid-based modeling
5. SHM in Action: hands-on experience
6. Probabilistic digital twins in SHM
7. The role of SHM for ancient bridges
8. Trending SHM topics: The role of transfer learning for SHM and the role of SHM for bridge adaptation to climate change
9. Limitations, grand challenges, and trends

In-person lectures

1. Field instrumentation
2. Risk and resilience
3. Value of information
4. Probabilistic FE modeling
5. Vision-based monitoring
6. SHM in Action (lab and field activities)

Instructors

• Eloi Figueiredo, Lusófona University, Portugal
• Ionut Moldovan, Lusófona University, Portugal
• Luís Oliveira Santos, National Laboratory of Civil Engineering, Portugal
• Marek Salamak, Silesian University of Technology, Poland
• Marcin Jasiński, Silesian University of Technology, Poland
• Maria Pina Limongelli, Politecnico di Milano, Italy
• Michael Havbro Faber, Lusófona University, Portugal
• Mihai Nedelcu, Technical University of Cluj-Napoca, Romania
• Pier Francesco Giordano, Politecnico di Milano, Italy
• Roland Kromanis, University of Twente, Netherlands

Invited Instructors

• João Canto, Lusófona University, Portugal
• Luca Pèla, Barcelona Tech - UPC, Spain
• Nuno Peres, Lusófona University, Portugal
• Nuno Santos, Lusófona University, Portugal
• Semih Gonen, Barcelona Tech - UPC, Spain

Institutional Support

• DEWESoft - measurement innovation

General Schedule

In-Person Schedule (July 14-18, 2025)

Testimony from the 1st edition in 2023