Short Course | Structural Health Monitoring | Belgium

A 12-hour blended short course designed to pose the structural health monitoring (SHM) in the context of a statistical pattern recognition paradigm to support the damage identification process and risk-informed integrity management. This course is organized in the context (one day before) of the IABSE Congress Ghent, on August 26, 2025. Registration is already available here.

The remote part introduces the concept of SHM and accelerates the learning process, while the in-person part focuses on bridging the gap between research and practical application. The techniques are shown with hands-on experiences applied to bridges. Unsupervised learning techniques as Gaussian mixture Models; supervised learning algorithms like artificial neural networks or support vector machines; and transfer learning methods as the transfer component analysis are all covered. The role of SHM to support the climate change adaptation of bridges is also discussed. 

Target public: The course is tailored towards graduate students and/or practicing engineers working full-time in public and private institutions, like authorities and contractors.

Accreditation: This short course has been accredited by Ordem dos Engenheiros - the Portuguese regulatory and licensing body for the engineering profession in Portugal.

Sustainable Development Goals: This course contributes to the Sustainable Development Goals (SDGs) 7, 9, and 13, by promoting sustainable and resilient infrastructure through the introduction of new technologies and innovation to guarantee the safety and comfort of people, through optimization of design and integrity management to reduce embedded CO2 and thereby countering climate change, and finally by along the same lines facilitating the development and operation of sustainable energy infrastructure, like wide turbines and dams.

REGISTRATION

Cost of attending the training is €475, which includes lunch and coffee-breaks. You can make the registration here. Registration is mandatory to prepare material, receipts, and certificates.

SPECIFIC OBJECTIVES

• Pose the SHM in the context of a statistical pattern recognition paradigm.
• Understand the differences between quasi-static and dynamic monitoring.
• Overview of sensors and DAQ hardware for designing an optimum instrumentation scheme for SHM.
• Understand the applicability of finite element modeling and machine learning (unsupervised and supervised learning) for data enhancement and interpretation as well as for damage identification.
• Understand the role of SHM to support climate change adaptation.
• Pose the concept of probabilistic digital twins in the context of SHM.
• Understand the role of SHM to support risk-informed integrity management.
• Understand the goal of SHM with current limitations, grand challenges, and future trends.

DURATION, LOCATION, DATE, AND TIME

• Duration: 12 hours
• Remote component (6h)
• In-person component (6h):
  • Location: Ghent, Belgium
  • Date: August 26, 2025
  • Time: 9:00 am to 16:00 (one hour for lunch)

COURSE SYLLABUS

OBSERVATIONS

• The instructors reserve the right to modify the course organization as necessary to maintain the highest standards of content quality.
• Course notes will be distributed during the course.
• A Certificate of Attendance will be issued at the end of the short course.
• If you have any questions, please send us an email: Este endereço de email está protegido contra piratas. Necessita ter o JavaScript autorizado para o visualizar.