Laboratory for Dynamics of Machines and Structures

High-speed Image Based Experimental Modal Analysis & Open Source Tools

Free Online Course

Due to the current conditions regarding the COVID-19 pandemic, our 2nd summer school on high-speed image based experimental modal analysis is postponed until next year.

Instead, we are pleased to offer a free short online course to anyone intereseted in the topic.

The course will be held in two parts, on June 29th and July 1st 2020.

Preliminary program

  1. Monday, June 29th, 3:00 p.m. to 5:00 p.m. CET: Selected open-source Python tools for structural dynamics (Scipy, pyFRF, pyEMA).
  2. Wednesday, July 1st, 3:00 p.m. to 5:00 p.m. CET: High-speed based EMA powered by open-source Python tools.

Target audience

PhD or final year MSc students working in the field of structural dynamics.

Prior knowledge

The Python programming language will be used throughout the course. Basic knowledge of Python is expected. The users of Matlab should be able to quickly catch up.

Course fee

This is a free course.

We hope that you find it useful, and we invite you to follow our work, and consider our summer school, where we explore these topics more extensively.

Application

You can apply by filling in the following registration form.

Relevant Scientific References

For scientific articles on image based EMA, please see our web site, especially papers:
         

Course material and templates

You can find interactive templates, along with more information on how to run the code and follow the course, in the sdPy GitHub repository.

Selected open source references

Contact

For further information please contact us at janko.slavic@fs.uni-lj.si
Instructors

Professor

Janko Slavič, PhD

  janko.slavic@fs.uni-lj.si
  +386 1 4771 226
jankoslavic     jankoslavic    

Professor

Miha Boltežar, PhD

  miha.boltezar@fs.uni-lj.si
  +386 1 4771 608

Assistant

Domen Gorjup, PhD

  domen.gorjup@fs.uni-lj.si
  +386 1 4771 227
domengorjup    

Assistant

Klemen Zaletelj, PhD

  klemen.zaletelj@fs.uni-lj.si
  +386 1 4771 228
klemengit