A New Performance Degradation Evaluation Method Integrating PCA, PSR and KELM

In order to better characterize the performance degradation trend of rolling bearings, a new performance degradation evaluation method based on principal component analysis (PCA), phase space reconstruction (PSR) and kernel extreme learning machine (KELM), namely PAPRKM is proposed to evaluate the p...

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Veröffentlicht in:	IEEE access 2021, Vol.9, p.6188-6200
Hauptverfasser:	Lv, Mingyang, Zhang, Chunguang, Guo, Aibin, Liu, Fang
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Degradation Delay time Feature extraction Indexes kernel extreme learning machine Machine learning Performance degradation performance degradation trend prediction Performance evaluation Performance prediction phase space reconstruction Prediction models Principal component analysis Principal components analysis Redundancy Roller bearings Rolling bearing Rolling bearings Time domain analysis Time series Vibration Vibrations
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