Bachelor-/Masterthesis: Simulative design of a condition monitoring system for plain bearings based on temperature field measurement

The Institute for Machine Elements and Systems Engineering (MSE) and Chair for Wind Power Drives (CWD) research the fundamental structural and tribological behavior of machine elements. One of the research objectives is to increase the availability, robustness and energy efficiency of wind turbines and to reduce the energy costs. For this experiment’s with software simulation tools and modern test benches are combined.

In order to reduce the power generation costs of modern wind turbines (WTG), the power density of the planetary gearboxes in WTGs is to be increased. The use of plain bearings, which have already been used in industry for a number of years, is a suitable solution. To date, however, there is no real-time capable condition monitoring system (CMS) to predict and avoid critical operating points at an early stage. The CWD and MSE are therefore conducting research into a modern CMS network that utilises temperature field measurements among others. This method is successfully applied to radial plain bearings and now being transferred to planetary plain bearings.

The aim of this thesis work is to determine suitable sensor positions for temperature measurement using a novel simulation tool chain based on thermal simulations of plain bearings.

Tasks:

• Familiarization with the topic of planetary plain bearings, and temperature field measurement (TFM)
• Simulation of EHD and FEM models of plain bearing test rigs
• Using existing tool chain, to calculate temperature distribution in plain bearing
• Evaluating sensor positions based on measurement sensitivity and proximity to running surface

Your profile:

• Motivation to work on a futuristic tool chain that can help predict plain bearing safety
• Interest in plain bearing technology, wind energy,
• Previous knowledge of Matlab and Python would be desirable
• First experiences with multi-body simulation programs like AVL Excite (EHD) and Abaqus (FEM) would be advantageous

What we offer:

• Independent and self-learning mode of work to bring the best out of you
• Scientific work in a highly motivated research team with a very good working atmosphere and intensive supervision
• Fun team events and network building
• Learning practice-relevant automated simulation methods
• Immediate start possible and flexible working hours
• Working on trending and future oriented problems

We look forward to your application by email:

Anuj Khare, M. Sc. RWTH
Chair for Wind Power Drives

Campus-Boulevard 61, 52074 Aachen
anuj.khare@imse.rwth-aachen.de