[Best Paper]A Feature Fusion-based Prognostics Approach for Rolling Element Bearings
Published in 5th International Conference on Materials and Reliability Jeju, Korea, 2019
A Rolling element bearing (REB) is the heart of rotating components; however, its failure can have daunting effects; hence the need for accurate condition monitoring and prognostics. In view of achieving a more comprehensive condition assessment and prognostics of rolling element bearings, this study proposes a kernel principal component analysis (KPCA) feature fusion technique for degradation assessment, and a deep learning model for prognostics. 
Recommended citation: U. E. Akpudo and J. H. Hur, “A Feature Fusion-based Prognostics Approach for Rolling Element Bearings,” 5th International Conference on Materials and Reliability Jeju, Korea, Nov. 27-29, 2019.
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