101-0008-00L Structural Identification and Health Monitoring
| Semester | Spring Semester 2022 |
| Lecturers | E. Chatzi, V. Ntertimanis |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Abstract | This course will present methods for structural identification and health monitoring. We show how to exploit measurements of structural response (e.g. strains, deflections, accelerations) for evaluating structural condition, with the purpose of maintaining a safe and resilient infrastructure. |
| Learning objective | This course aims at providing a graduate level introduction into the identification and condition assessment of structural systems. Upon completion of the course, the students will be able to: 1. Test Structural Systems for assessing their condition, as this is expressed through measurements of dynamic response. 2. Analyse vibration signals for identifying characteristic structural properties, such as frequencies, mode shapes and damping, based on noisy measurements of the structural response. 3. Formulate structural equations in the time and frequency domain 4. Identify possible damage into the structure by picking up statistical changes in the structural behavior |
| Content | The course will include theory and algorithms for system identification, programming assignments, as well as laboratory and field testing, thereby offering a well-rounded overview of the ways in which we may extract response data from structures. The topics to be covered are : 1. Elements of Vibration Theory 2. Transform Domain Methods 3. Digital Signals (P 4. Nonparametric Identification for processing test and measurement data (transient, correlation, spectral analysis) 5. Parametric Identification (time series analysis, transfer functions) A series of computer/lab exercises and in-class demonstrations will take place, providing a "hands-on" feel for the course topics. Grading: - This course offers optional homework as learning tasks, which can improve the grade of the end-of-semester examination up to 0.25 grade points (bonus). - The learning tasks will be taken into account if all 3 homeworks are submitted. The maximum grade of 6 can also be achieved by sitting the final examination only. |
| Lecture notes | The course script is composed by the lecture slides, which are available online and will be continuously updated throughout the duration of the course: Link |
| Literature | Suggested Reading: T. Söderström and P. Stoica: System Identification, Prentice Hall International: http://user.it.uu.se/~ts/sysidbook.pdf |
| Prerequisites / Notice | Familiarity with MATLAB is advised. |