The programme is divided in two days:

Thursday 10 Sep. 2020 from 8h30 until 18h10 and Friday 11 Sep. 2020 from 8h30 until 17h00

### Course programme

Basic assumptions. Single and multiple degree of freedom systems. Undamped systems, proportionally and generally viscously damped systems. Frequency response function approach. Natural frequencies, damping factors, residues, modal vectors, modal participation factors, modal mass, modal stiffness, modal scaling.

Basic assumptions. Single and multiple degree of freedom systems. Undamped systems, proportionally and generally viscously damped systems. Frequency response function approach. Natural frequencies, damping factors, residues, modal vectors, modal participation factors, modal mass, modal stiffness, modal scaling.

Signal types, Fourier transforms: definition and properties, related transforms. Sampling and A/D conversion, leakage errors and windows, aliasing errors and filters. Autocorrelation and autopower. Crosscorrelation and crosspower. Averaging. Frequency response function estimation: H1, H2 and Hv, coherence function.

Excitation systems, excitation hammers. Force transducers, motion transducers, transducers mounting, calibration. Measurement and analysis systems.

Signal types: random, sine, pulse. Signal performance and limitations. Application on linear and non-linear systems. Multiple input/output testing.

Review and principles, frequency and time domain methods, single and multiple degree of freedom systems, local and global estimates, system order estimation tools, stability diagram, some specific methods: least squares complex exponential, least squares complex frequency domain, least squares frequency domain. Interpretation of results.

Error sources, non-linearities, modal assurance criterion, mode overcomplexity, mode colinearity, frequency response function synthesis.

Principles and application areas of the use of modal parameters in trouble shooting, forced response estimation, sensitivity analysis and structural dynamics modification and assembly.

Correlation between numerical and experimental models, model matching, model updating. Using numerical model information for improved test set-up design.