101-0008-00L  Structural Identification and Health Monitoring

SemesterSpring Semester 2020
LecturersE. Chatzi, V. Ntertimanis
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
101-0008-00 GStructural Identification and Health Monitoring
Remark: Former title Identification Methods for Structural Systems (before in HS).
2 hrs
Wed14:45-16:30HIL E 8 »
15:00-17:00ER SA TZ »
E. Chatzi, V. Ntertimanis

Catalogue data

AbstractThis course will present methods for assessing the condition of structures based on monitoring. The term "monitoring" corresponds to measurements of structural response (e.g. strains, deflections, accelerations), which are nowadays available from low-cost and easily deployed sensor technologies. We show how to exploit sensing technology for maintaining a safe and resilient infrastructure.
ObjectiveThis 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 stiffness
2. Analyse sensor signals for identifying characteristic structural properties, such as frequencies, mode shapes and damping, based on noisy or incomplete measurements of the structural response.
3. Establish relationships governing structural response (e.g. dynamics equations)
4. Identify possible damage into the structure by picking up statistical changes in the structural "signature" (behavior)
ContentThe 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. Fundamentals of dynamic analysis (vibrations)
2. Fundamentals of signal processing
3. Modal Testing for determining the modal properties of Structural Systems
4. Parametric & Nonparametric Identification for processing test and measurement data
i) in the frequency domain (Spectral Analysis, Frequency Domain decomposition)
ii) in the time domain (Autoregressive models, the Kalman Filter)
5. Damage Detection via Stochastic Methods

A comprehensive series of computer/lab exercises and in-class demonstrations will take place, providing a "hands-on" feel for the course topics.

Grading:
The final grade will be obtained, either
- by 30% from the graded exercises and 70% from the written session examination, or
- by the written session examination exclusively.
The highest ranking of the above two options will be used, so that assignments are only used to strengthen the grade.
Lecture notesThe course script is composed by the lecture slides, which are available online and will be continuously updated throughout the duration of the course: Link
LiteratureSuggested Reading:
T. Söderström and P. Stoica: System Identification, Prentice Hall International: Link
Prerequisites / NoticeFamiliarity with MATLAB is advised.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersE. Chatzi, V. Ntertimanis
Typeend-of-semester examination
Language of examinationEnglish
RepetitionA repetition date will be offered in the first two weeks of the semester immediately consecutive.
Additional information on mode of examinationThis 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.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Civil Engineering MasterMajor in Structural EngineeringWInformation