Structural Vibrations (XVib1)
Bachelor – 5 ECTS
Web: https://odin.sdu.dk/sitecore/index.php?a=searchfagbesk&bbcourseid=T030016101-1-E25&lang=en
This course provides a foundation in the analysis of vibrating mechanical systems. Students learn to establish governing equations of motion using Newton’s law, Lagrange’s equation, stiffness and flexibility methods, and explore free and forced vibrations in discrete and continuous systems. Key topics include modal analysis, damping, and transverse, longitudinal, and torsional vibrations. Practical exercises focus on determining natural frequencies, mode shapes, and building mathematical models for real-world structures.
System Identification Methods for Structural Dynamics (MK-SydID)
Master – 10 ECTS
Web: https://odin.sdu.dk/sitecore/index.php?a=searchfagbesk&bbcourseid=T170009101-1-F26&lang=en
This course introduces advanced methods for analysing and identifying dynamic behaviour in mechanical systems. Students learn to model multi-degree-of-freedom (MDOF) systems, perform frequency and modal analysis, and simulate responses under deterministic and stochastic excitations. Key topics include power spectral density (PSD) and frequency response function (FRF) estimation, parametric time-series modelling, and modal identification using frequency-domain and stochastic subspace methods. The course also covers validation and updating of finite element models and substructuring techniques. Practical exercises emphasize computational tools and experimental data analysis for real-world applications.
Machine Learning Methods for Monitoring of Structures
Master – 5 ECTS
Web: https://odin.sdu.dk/sitecore/index.php?a=searchfagbesk&bbcourseid=T020055101-1-F24&lang=en
This course explores system identification and machine learning techniques for diagnosing damage in structures and machines, with a focus on vibration-based methods. Students learn to design algorithms for damage detection and localization, considering environmental and operational variability. Topics include feature extraction, novelty detection, regression, classification, and clustering methods, time-series modelling, and strategies for compensating variability. Practical exercises emphasize applying these tools to real-world structural dynamics data.
Rotor Dynamics
Master – 5 ECTS. Not offered currently.
This course introduces the physical principles and modelling techniques for rotating machinery. Students learn rotor dynamics, including whirling vibration, critical speeds, gyroscopic effects, and dynamic balancing, as well as the fundamentals of bearings and machine components. The course covers model reduction, damage detection methods, and practical implementation using MATLAB, LabVIEW, and FEM tools. Emphasis is placed on analysing and solving real-world machine dynamics problems and designing rotor systems for industrial applications.