Adapting geometry-based polygonal contacts for simulating faulty rolling bearing dynamics

Abstract

Rolling bearings are a leading cause of equipment breakdowns in electrical machines, underscoring the significance of predictive maintenance strategies. However, the given methods require high-quality big data, which is challenging to acquire, especially for faulty cases. Simulation models offer an alternative by generating large datasets to complement experimental data. However, bearings involve complex contact-related phenomena, such as slipping and clearance. Therefore, generating realistic data comparable to the real-world necessitates accuracy. Our study presents a multibody simulation system of a motor bearing, incorporating a geometry-based polygonal contact method (PCM), which accurately captures nonlinear bearing dynamics and allows for the simulation of various contact geometries. We introduce a systematic approach to adjust the PCM contact properties for rolling bearings, referencing the well-established Hertzian theory. Both healthy and faulty bearings with a local outer ring fault were simulated. The simulated output was a relative shaft displacement, experimentally validated using a capacitive sensor. Our model successfully demonstrates the potential to employ geometry-based contacts for generating realistic data on faulty bearings with the aim of predictive maintenance.