Fault Diagnosis in Flywheels: Case Study of a Reaction Wheel Dynamic System with Bearing Imperfections

This study is intended to highlight the importance of flywheels, in particular reaction wheels and steps that can be taken to ensure that they remain in stable condition for the duration of their mission. While there is an ample amount of work on this topic, this study provides an easy to follow innovative two step approach to tackle the said issue and a starting point for a different kind of analysis based on vibrations. The proposed methodology starts by obtaining the vibration data to be analyzed and applying a data based feature extraction technique known as Stochastic Resonance (SR) to the data. SR is a fairly novel tool which has shown a lot of promise in the context of mechanical systems fault diagnosis. The results obtained from the application of SR to the data is usually in the time domain but is converted to the frequency domain to reveal more information which can be used to take appropriate corrective action. As a safeguard, vibration suppression using nonlinearity which is an emerging tool is applied as a second step, to counteract whatever vibrations that may occur, thus leading to a more stable reaction wheel system.