Artifical Intelligence based Time Series Analysis and Prediction for Condition Monitoring

Institut
Lehrstuhl für Maschinenelemente
Typ
Bachelorarbeit / Semesterarbeit / Masterarbeit /
Inhalt
theoretisch /  
Beschreibung

Motivation:
At the Gear Research Centre we are developing an innovative artificial intelligence based condition monitoring system with gear damage detection based on various measured time series data. With the benefit of having a large test facility, we are able to run as many tests as necessary to get the huge amount of data needed.

Your task:
The goal of this project is to develop and implement advanced neural networks for time series data ML. Based on various test data (e.g. acceleration) you will develop a ML pipeline to detect the degree and characteristics of gear damages. Furthermore, you will use the data of industrial tests to advance neural network models for damage prediction.

Voraussetzungen
  • Highly interested in artificial intelligence with advanced knowledge of neural networks
  • Understanding of Time Series ML
  • Coding Skills (e.g. Python, TensorFlow)
  • Highly motivated and responsible
  • Fluent in English or German
Möglicher Beginn
sofort
Kontakt
M.Sc. Stefan Sendlbeck
Raum: MW 2513
Tel.: +49 89 289 15876
sendlbeckfzg.mw.tum.de
Ausschreibung