When Linear RUL Labels Disagree with Vibration Degradation: A Stage-Aware Target and Dual-Scale Predictor Evaluated on XJTU-SY and IMS
Why bearing failure timelines don't match what vibration sensors actually show
Machines fail in predictable stages—but the standard way of labeling remaining lifespan (as a straight line over time) doesn't match what vibration sensors actually measure. Researchers built a new prediction system that accounts for three distinct failure phases, fitting a curve that bends to match real vibration behavior. On test bearings, this stage-aware approach cut prediction error by 10–15% compared to the traditional linear method.
Industrial bearing failures cause unplanned downtime and expensive repairs. Better predictions of when a bearing will actually fail—rather than guesses based on calendar time—let maintenance teams act at the right moment: not so early that they waste money on premature replacement, not so late that the machine breaks down. This method shows that off-the-shelf sensors can be more useful if the software interpreting them accounts for how machines truly degrade.