B8953 - STRUCTURAL MONITORING AND IDENTIFICATION M

Learning outcomes

The aim of this course is to introduce students to the basic aspects of Structural Health Monitoring (SHM), with a particular emphasis on static and vibration-based methods for damage detection in historic structures. It covers techniques for analyzing structural response data, such as strains, deflections, and accelerations, to assess structural conditions and support the maintenance of buildings and structures. Students will acquire knowledge on the following areas: basic concepts of SHM and its applications; data acquisition, data processing, treatment of uncertainties; development of data driven and model-based methods for damage identification. Case studies will be presented, and laboratory activities will be performed to critically assess advantages and drawbacks of the methodologies presented in the theoretical lectures.

Course contents

The course covers the fundamental principles and methodologies of Structural Health Monitoring (SHM) for existing and historic structures. The main topics include:

• Introduction to Structural Health Monitoring (SHM): objectives, monitoring strategies, applications to existing and historic structures, and the role of monitoring in structural assessment and maintenance.

• Static and dynamic measurement systems: principles and operating characteristics of sensors for displacement, strain, acceleration, temperature, and environmental variables; data acquisition systems; advanced sensing technologies.

• Fundamentals of vibration-based structural identification: recap on fundamentals of dynamic behaviour of structures, free and forced vibrations, modal properties, damping, and dynamic response under ambient and operational excitations. Structural identification: principles of experimental and operational modal analysis, signal processing, modal parameter estimation, vibration-based damage detection, and introduction to model-based and data-driven identification methods.

• Fibre optic monitoring: principles of fibre optic sensing for structural monitoring, including distributed and quasi-distributed measurements; main types of fibre optic sensors, such as Fiber Bragg Grating (FBG) sensors and distributed sensing systems; measurement of strain, temperature, and deformation fields; installation strategies, data interpretation, and applications.

• Computer vision techniques for structural monitoring: principles and applications of image-based monitoring techniques, with particular focus on Digital Image Correlation (DIC); acquisition and processing of image sequences; full-field displacement and strain measurements; motion tracking, deformation assessment, and crack detection.

• Applications to historic structures: examples of monitoring systems and interpretation of monitoring data for masonry buildings, towers, bridges, and monuments.

Readings/Bibliography

Lecture notes, slides, scientific papers, and laboratory material provided by the instructors constitute the primary study material. Additional references include:

• Brownjohn, J.M.W. (2007). Structural health monitoring of civil infrastructure. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 365(1851), 589–622.

• Farrar, C.R., & Worden, K. (2007). An introduction to structural health monitoring. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 365(1851), 303–315.

• Rainieri, C., & Fabbrocino, G. (2014). Operational Modal Analysis of Civil Engineering Structures. Springer.

• Glisic, B., & Inaudi, D. (2007). Fibre Optic Methods for Structural Health Monitoring. Wiley.

• Sutton, M.A., Orteu, J.-J., & Schreier, H. (2009). Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts, Theory and Applications. Springer.

Additional scientific papers and technical reports related to structural monitoring, system identification, and applications to historic structures will be provided during the course through the University's online learning platform.

Teaching methods

The course combines theoretical lectures with practical and experimental activities. Classroom lectures are supported by multimedia presentations and live demonstrations using small scale demonstrators; numerical software for structural modelling, data processing, and structural identification, will be used.

Hands-on experiments will be carried out during the lectures to illustrate the operation of monitoring systems, sensing technologies, and data acquisition procedures. Students will also visit the Structural Engineering laboratories @DICAM to become familiar with experimental equipment and testing facilities.

The course includes experimental activities on full-scale (1:1) structural specimens, allowing students to acquire practical experience in structural monitoring, dynamic testing, and interpretation of experimental data.

Assessment methods

The final assessment is based on a group project developed during the course by teams of up to four students.

Each group will be assigned a Structural Health Monitoring case study or an application topic related to the course contents. Students are required to analyse the assigned problem, critically discuss the adopted methodologies, and present the obtained results.

The assessment consists of the oral presentation and discussion of the project. Evaluation will consider the technical quality of the work, the understanding of the underlying theoretical concepts, the ability to critically interpret the results, the effectiveness of the presentation, and the contribution of each student to the group activity.

Teaching tools

Teaching activities are supported by multimedia presentations, lecture notes, and scientific papers made available through the University's online learning platform. The course makes use of numerical code/software for signal processing, structural identification, and data analysis. Laboratory activities are carried out using monitoring instrumentation, including static and dynamic sensors, data acquisition systems, fibre optic sensing devices, and Digital Image Correlation (DIC) equipment. Experimental activities are conducted both in the Structural Engineering laboratories and on full-scale structural specimens.

Office hours

See the website of Alessandro Marzani

See the website of Antonio Palermo

See the website of Nicola Buratti