Student* with Master Thesis (optional) AI-Based Blade Bearing Condition Mon

at  Wind Energy Systems

The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research units throughout Germany and is a leading applied research organization. Around 32 000 employees work with an annual research budget of 3.4 billion euros.

WHO WE ARE …

Our primary focuses at Fraunhofer IWES are on wind energy and hydrogen technologies. Our institute is home to more than 300 scientists and employees as well as over 100 students from over 30 countries pursuing careers in applied research and development at nine sites. We secure investments in technological developments through validation, shorten innovation cycles, accelerate certification procedures, and increase planning accuracy by means of innovative measurement methods.

WHAT WE CAN OFFER YOU …

We offer various opportunities to join us as a student. Whether it is an internship, where you gain a comprehensive insight into the areas of work, or the role of a student assistant, which is easy to combine with your studies. Are you looking for an exciting topic for your thesis and do you want to delve deeply into a topic scientifically? Together, we will find the right path for you! We know that studying can also be very demanding and requires a certain level of flexibility. That is no problem here, as – in agreement with your colleagues – you can decide flexibly what days and hours to work. Temporarily, you can even work remotely, depending on the job.

THESE DUTIES AWAIT YOU …

You will be involved in conducting a literature review on state-of-the-art methods for condition monitoring of blade bearings in wind turbines. Furthermore, you will focus on identifying additional suitable AI approaches for blade bearing applications and data preprocessing (feature engineering). Subsequently, you will systematically evaluate the most promising approaches identified in the literature review. Numerous datasets from previously conducted bearing tests with various types of damage will be available for this purpose. The objective is to assess the suitability of these approaches for detecting early bearing damage. You will prepare comprehensive documentation of the results.