Entwicklung eines generischen Kinematik-Getriebemodells für die Synthese komplexer Sensordaten


Health and Usage Monitoring Systems (HUMS) are used to monitor the condition of helicopter systems and components and are fundamental for the implementation of predictive maintenance strategies. The focus is particularly on critical systems such as the drive train. In the future, data-based (machine learning) algorithms will be increasingly used to evaluate sensor data from HUMS in order to enable predictive analytics. Initially, these algorithms can be developed and assessed perfectly based on simulated training data.

Thesis Content:

The aim of this thesis is the development of a generic kinematic gearbox model. This model should enable the synthesis of complex sensor data with a special focus on vibration data. For this purpose, the theoretical background of gearbox design and modeling shall be researched first. Subsequently, the model will be developed and first data will be synthesized.


  • Literature research on gearbox design parameters and modeling methods
  • Analysis of the gear system and definition of requirements
  • Development of the generic gearbox model with focus on modularity
  • Integration of sensors and data synthesis

Organizational matters and requirements:

  • Begin: as of now
  • Can be written in German or English
  • Interest in gearboxes and high motivation
  • Preferred: Basic experience with MATLAB or Python, knowledge about gearbox mechanics