Publications and Presentations

Elastic waves in bearing raceways: the forward and inverse problem

Jessica J Kent, Matheus de C. Loures, Art L. Gower

Abstract:

Turbines are crucial to our energy infrastructure, and ensuring their bearings function with minimal friction while often supporting heavy loads is vital. Vibrations within a bearing can signal the presence of defects, friction, or misalignment. However, current detection methods are neither robust nor easy to automate. We propose a more quantitative approach by modelling the elastic waves within bearing raceways. By approximating the raceway as a hollow cylinder, we derive straightforward 4x4 systems for its vibrational modes, enabling both forward and inverse problem-solving. We also demonstrate how to significantly reduce the number of required sensors by using a simple prior: the known number of rollers and their angular speed. We present numerical examples showcasing the full recovery of contact traction between bearings and the raceway, as well as the detection of elastic emissions.

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  • arXiv

    • A tomographic method to predict forces in a rolling element bearings (ISMA 2024)

    Jessica J Kent, Matheus de C. Loures, Art L. Gower

    Abstract:

    Typically methods to detect defects in roller bearings rely on measuring vibrations. There has been a lot of work on signal processing to get the clearest sign of defects appearing on different components. Here we ask how can modelling the elastic waves in the raceway, or other cylindrical components, improve methods that monitor roller bearing vibrations. One clear improvement is that we can predict stress profile on the raceway. By describing and solving for the elastic waves we first deduce a method for elastic tomography in a cylindrical case. Then, to significantly reduce the number of sensors required, we show how to use prior information of the source of vibration, such as the contacts from the rollers. We some examples of recovering the traction profile in the bearing raceway.

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