Bachelor / Master thesis: Analysis and evaluation of electrical impedance measurement data to identify failure-critical operating conditions of plain bearings in wind turbines

The Chair for Wind Power Drives researches the behaviour of drive systems in modern multi-megawatt wind turbines. The research objectives are to increase the availability, robustness and energy efficiency of wind turbines and to reduce the levelized cost of energy. State-of-the-art engineering software and system test benches are used for this purpose.

In order to reduce the power generation costs of modern wind turbines (WTs), the power density of the planetary gearboxes in WTs 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 failure-critical operating points at an early stage.

Research is therefore being conducted at the CWD on an innovative CMS network that utilizes, among others, the surface acoustic wave technology. This technology shows great potential but requires further validation through comparative measurements. To this end, electrical impedance measurements will be performed at the component level to detect relevant events such as the transition point from liquid friction to mixed friction.

The aim of this thesis is a systematic analysis and evaluation of the measurement data obtained through impedance measurements.

Yor tasks:

• Familiarization with the measurement technology and measurement method (electrical impedance measurement)
• Conducting and assisting with impedance measurements on the component test bench
• Development of evaluation methods
• Analysis and comparison of impedance measurement data with measurement results from other sensor technologies

Requirements:

• Motivation to work independently and on one’s own responsibility, ability to communicate and work in a team, as well as a secure command of the German or English language
• Interest in wind energy, gear and plain bearing technology
• Interest in data analysis
• Programming experience in Python desirable

What we offer:

• Scientific work in a highly motivated, interdisciplinary team
• Work on a topic with high industrial relevance
• Exciting combination of theory and practice
• Pleasant working atmosphere and intensive supervision
• Option to participate in a scientific publication
• Immediate start possible

We look forward to your application by email:

Tim Scholz, M. Sc. RWTH
Chair for Wind Power Drives

Campus-Boulevard 61, 52074 Aachen
tim.scholz@cwd.rwth-aachen.de