Dein Alltag besteht darin, Methoden zur Zustandsüberwachung von Wellenlagern zu analysieren. Dabei identifizierst du geeignete KI-Ansätze, bewertest sie anhand vorhandener Datensätze und dokumentierst die Ergebnisse sorgfältig.
Anforderungen
- •Studying a technical or engineering degree
- •Experience using Python
- •Basic knowledge in artificial intelligence
- •Basic knowledge in machine learning
- •Solid mathematical understanding
- •Solid technical understanding
- •English language skills
Deine Aufgaben
- •Literaturrecherche zu Methoden der Zustandsüberwachung von Wellenlagern
- •Geeignete KI-Ansätze für Wellenlageranwendungen identifizieren
- •Datenvorverarbeitung und Merkmalsengineering durchführen
- •Vielversprechende Ansätze systematisch bewerten
- •Verfügbare Datensätze zu Lagertests mit verschiedenen Schäden nutzen
- •Eignung der Ansätze zur Frühschadenserkennung beurteilen
- •Umfassende Dokumentation der Ergebnisse vorbereiten
Deine Vorteile
Verschiedene Einstiegsmöglichkeiten als Student
Praktika mit umfassendem Einblick
Rolle als studentische Hilfskraft
Unterstützung bei Abschlussarbeiten
Flexibilität bei Arbeitszeit und -tag
Temporäre Remote-Arbeit je nach Job
Original Beschreibung
City:
Hamburg
Date:
Mar 8, 2025
# Student with Master Thesis (optional) AI-Based Blade Bearing Condition Monitoring
**This team needs your support ...**
You will be part of the group »Slewing Bearings« at our site in Hamburg. At present, our team consists of 10 employees and several students. We focus on large slewing rings. To meet the highest reliability standards for wind turbines, small and large-scale bearing test rigs are developed and operated at the Large Bearing Laboratory. Regardless of projects and backgrounds, we support each other, and open communication and collaboration are important to us. Become an active member of the team; we are keen to hear your ideas! As an international oriented IWES-team, we highly appreciate an open exchange, whether this be in German or English. Respectful cooperation is also very important to us. You are wondering what you can bring to the team?
**What you will do**
**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.
**What you bring to the table**
**What is your background?**
Are you studying a technical or engineering degree such as Mechanical Engineering, Wind Energy Technology, Mechatronics, Computer Science, or a similar field? Do you have experience using Python and speak English? Do you have basic knowledge in artificial intelligence and machine learning, along with a solid mathematical and technical understanding? Great!
**What you can expect**
**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.
We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.
The standard contract duration is 1 year, individual agreements are possible. The working time consists of up to 80 hours per month. Remuneration according to the general works agreement for employing assistant staff.
**Job Segment:**
Wind Energy, Sustainability, Mechanical Engineer, Computer Science, Engineer, Energy, Engineering, Technology