Together we drive forward what matters most: We at the EnBW develop smart energy products that make our cities more sustainable and push the expansion of renewable energies forward. Therefore we need strong support – Join us now!
Masterand (w/m/d) Produktionsservice
bei der EnBW Energie Baden-Württemberg AG in Hamburg
At our company as student (m/f/d) you are part of the everyday working life. With us you can gain valuable experiences, carry responsibility, establish networks and pursue your personal development.
Structural health monitoring of offshore wind monopiles - Automated identification of modal Parameters
Structural health monitoring of offshore wind turbines allows an early detection of potential structural damages in order to safely operate offshore wind turbines. Good knowledge on the health of support structures is also beneficial to make informed decisions on lifetime extension of the assets at the end of their design lifetime (typically ~25 years).
The goal of this master thesis is to analyze the suitability of different operational modal analysis techniques to identify modal parameters of monopiles, such as natural frequencies, damping, and mode shapes. After a thorough literature review, three of the most prominent approaches (such as Frequency Domain Decomposition, Stochastic Subspace Identification, etc.) shall be implemented in the programming environment Python. An automated algorithm must be used to identify modal parameters from resulting stabilization charts. Performance of the algorithms is then tested with measurement data from EnBW’s offshore wind parks. A main challenge of the project will be to implement a robust preprocessing for large amounts of measurement data. If time allows, obtained modal parameters shall be evaluated statistically to investigate short- and long-term effects on the structural behavior.
Literature review on structural health monitoring and operational modal analysis applied for offshore wind turbines
Implementation of three selected operational modal analysis techniques in Python
- Development of an automated algorithm to identify modal parameters in Python
- Testing with measurement data from EnBW’s offshore wind parks
- Investigation of robust preprocessing algorithms for large data sets
- Optional: statistical evaluation of short- and long-term structural behavior
- Student of civil engineering, mathematics, physics, wind energy, data science, or similar
- Advanced programming skills in Python
- Good understanding of structural dynamics and modal analysis
- Technical knowledge of wind turbines is a plus
- Exiting tasks open diverse perspektives for your personel development
- We are distinguished by collegial teamwork and modern workplaces
- Flexible worktime allows compatibility of work and study
- Attractive offers for our employees are our strength
Did we catch your Attention? Apply now!
If any further questions occur, feel free to contact David Veith from the human resources department at firstname.lastname@example.org.
You can find our information on data protection for applicants (m/f/d) hier