Bearing the load
Bison code: L.28225
Bearings play a crucial role in all kinds of equipment containing rotating elements. Even though bearings are small and inexpensive, a bearing failure can lead to large costs due to downtime of machineries. Therefore it would be beneficial if it would be possible to predict if a bearing will fail in the nearby future. Taking it even further, predicting the remaining useful life of a bearing can provide even greater benefits as maintenance can be planned accordingly.
A common method for predicting bearing failures is by analysing data from sensors such as accelerometers, temperature and piezoelectric placed on the bearing housing itself. To further enhance the useability of this sensing approach, this project will focus on remote sensing techniques.
Goal of this project is to identify and verify which remote sensing techniques are viable for predicting bearing failure. Furthermore, determining the location where to measure is also still an open question. Remote sensing techniques which can be considered are computer vision, thermal camera, e-nose and a microphone array.
To execute this research project the Hague University of Applied Sciences have designed a test bench to collect data from bearings under various kinds of load. Students will work on identifying remote sensing techniques, determining where and how to place these sensors and do preliminary data analysis to verify the performance with respect to in-situ sensors.