Ira Lange
PhD
Diagnostics‑Driven Reduction of Uncertainty in Remaining Useful Life Prediction of Wind Turbine Blades
Host organisation
Delft University of Technology
Industry partner
Fraunhofer Society
Project Description
To improve wind turbine Operation & Maintenance, reliable tools for predicting the Remaining Useful Life (RUL) of rotor blades are needed. These can be based on physical or data‑driven models, which inherently involve uncertainty and limit confident decision‑making. This project aims to reduce prognostic uncertainty by leveraging diagnostic information. Diagnostic information is obtained through structural health monitoring techniques, such as Experimental Modal Analysis or Acoustic Emission sensing.
The diagnostic information will also be used to gain knowledge on how structural health degrades during operation, combining finite element analysis and structural testing. The findings will support the development of a diagnostics‑enhanced prognostics model with improved reliability.
Supervisors
Enno Petersen
Nick Eleftheroglou
Dimitrios Zarouchas
Background
I am originally from Verden, a small city in northern Germany, and studied at TU Delft and DTU within the Double Degree Master program European Wind Energy Master. During this time, I mainly focused on composites and structural design in wind, and in my thesis I optimized the structural layout of a rotor blade. Studying in Denmark and the Netherlands allowed me to learn in different academic environments and build nice multicultural friendships. In my free time, I like spending time near the water, swimming, scuba diving, or kayaking, and having cozy evenings with friends or a good book.
Motivation
Contributing to IntelliWind’s goal of advancing wind energy technology and contributing to sustainable energy production is very exciting for me. Since my long-term goal is to use my engineering knowledge to improve people’s living conditions and support a more sustainable future, I am happy to be a part of this research project.
Additionally, the multicultural environment in IntelliWind is important motivation for me. I greatly enjoyed working in international teams during my studies and am excited to be part of this unique Europe-wide reserch project, including academia and industry partners.
