Work

Fractional Long-Range Dependence Model for Remaining Useful Life Estimation of Roller Bearings

Year: 2025

Type: article

Abstract: Estimation of remaining useful life (RUL) of roller bearings is a prevalent problem for predictive maintenance in manufacturing. However, roller bearings are subject to a variety of factors during their operation. As a result, we deal with a slow nonlinear degradation process, which is long-range dependent, self-similar and has non-Gaussian characteristics. Proper data pre-processing enables us to use Pareto’s probability density function (PDF), Generalized Pareto motion (GPm) and its fractional-order extension (fGPm) as the degradation predictive model. Estimation of the Hurst exponent shows that this model has a long-range correlation and self-similarity. Through the analysis of the uncertainty of the end point of the bearing’s RUL and the prediction process, not only did it verify the high adaptability of fGPm in simulating complex degradation processes but also the criteria for judging self-similarity, and LRD characteristics were established. The case study mainly proves the validity of the theory, providing an effective analytical tool for a deeper understanding of the degradation mechanism.

Source: Fractal and Fractional

DOI: 10.3390/fractalfract10010012

Authors: Shoukun Chen, Piercarlo Cattani, Hongqing Zheng, Qinglan Zheng, Wanqing Song

Institutions: Minnan University of Science and Technology, Sapienza University of Rome

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,258

Funders: Fujian Provincial Department of Science and Technology, Quanzhou City Science and Technology Program