Bachelor/Master thesis: Artificial Intelligence (AI) solution for predicting the failure mechanisms of sliding bearings in maritime propulsion systems

The Institute of Machine Elements and System Engineering researches the fundamental structural and tribological behavior of machine elements and represents them in experimentally validated model descriptions. These model descriptions are used to analyse and design the functional, loss and noise behavior of entire technical systems with a focus on drive technology. The developed models are also used to research and develop methods of Model Based Systems Engineering as a central element of future inductive product development processes.

Due to the progressive climate change new shipping routes occur in the polar regions. This leads to an increasing number of collisions between ship propellers and sea ice which results in high impulse loads on the propeller and thus on the sliding bearings of the shaft. The influence of these loads on the bearing life is widely unknown.

The main objective of HealthProp is to improve operational safety in the Arctic and Antarctic by developing a digital twin solution for intelligent monitoring, main tenance and life prediction of marine propulsion systems in the ice ice. Therefore, this work focuses on developing an AI solution to detect the failure mechanism progression according to the operating conditions of the SA Agulhas II research vessel.

Tasks:

• Literature review review: Conduct a comprehensive review of the existing literature on calculation of sliding bearings as well as AI solution solutions
• Data set CollectionCollection: Collect and analyze the opration condations and the available simulation results (Define input and output variables)
• Feature Selection Selection: Select the most important features from thedata set for use in the predictive model.
• Model Development Development: Develop an AI AI-based model that can predict the failure mechanism of sliding bearings in maritime propulsion systems
• EvaluationEvaluation: Evaluate the model on the basis of the simulation Requirements

Requirements:

• Motivation to work independently and responsibly
• Interest in powertrain and simulation technology
• Prior knowledge in the field of mechanical systems as well as machine element design.
• Previous knowledge in the field of simulation and programming (e.g. MATLABATLAB/PYTHON ) is desirable, but not mandatory.

What we offer:

• Participation in an international research project
• Intensive support in a highly motivated and interdisciplinary team
• Learning of practice practice-relevant simulation methods
• Option to participate in a scientific publication
• Immediate start possible
• Flexible working hours

Auf deine aussagekräftige Bewerbung per E-Mail freut sich:

Ahmed Saleh, M. Sc.
Institut für Maschinenelemente und Systementwicklung

Schinkelstraße 10, 52062 Aachen
ahmed.saleh@imse.rwth-aachen.de