RUL Estimation for Rolling Bearings Using Augmented Quaternion-Based Least Mean P-Power With Correntropy Induced Metric Under Framework of Sparsity
Qing Li
Abstract
Accurate remaining useful life (RUL) estimation of rolling bearings can significantly improve the safety, availability, reliability and productivity of a rotating machinery system. In this article, a new approach of RUL estimation for rolling bearings based upon the fractional-order spatiotemporal sparse low-rank matrix (FST-SLRM) and augmented quaternion least mean p-power with correntropy induced metric (AQLMP-CIM) is originally proposed. Specifically, the proposed approach includes three modules: the construction of the fused health indicator, which fuses the classical features and spectral kurtosis derived indices; the decomposition of the static and dynamic components, the fused health indicator time series (FHITS) is decomposed by the FST-SLRM algorithm, thus low- and high- frequency trend components (i.e., LFCs, HFCs) are obtained, respectively; and the prognostics of degradation trajectory and RUL estimation, the degradation trajectories are obtained by the AQLMP-CIM algorithm via integrating the predicted LFC and HFC, and the RUL is eventually acquired. Two experimental cases are conducted on run-to-failure fatigue test of rolling bearings, the results demonstrate that the proposed approach is able to achieve better performance compared with state-of-the-art benchmarks.