A new holistic approach to investigating and estimating rolling bearing RUL based on physical grounds

Rolling bearings are critical components in rotating machinery. Throughout their operational life, they endure periodic loading cycles that could lead to the formation of spalls. While current capabilities enable early detection of incipient spalls, which helps prevent catastrophic failure of the machine, to utilize the entire operational life of the bearings, it is essential to estimate their spall severity and remaining useful life. Using physics-based models and experimental results, this article introduces an integrative approach. We develop a new conceptual framework for monitoring bearing health, assessing defect severity by identifying physical processes that govern defect evolution, and predicting bearing failure in real-world applications. The framework incorporates four models: the dynamic model, oil debris monitoring (ODM) model, damage model, and finite element model, along with experimental work, including vibration analysis, ODM data, and strain measurements using fiber Bragg grating sensors. The integration of experimental work with these models provides condition and health indicators for both diagnosis and prognosis. By using this model, the research community can gain a deeper understanding of spall propagation mechanisms, which will result in better predictions regarding the remaining useful life of rolling bearings.