Fault diagnosis of rotating machinery using Gaussian process and EEMD‐treelet

DOI10.1002/ACS.2952zbMath1407.93364OpenAlexW2902018800WikidataQ128872485 ScholiaQ128872485MaRDI QIDQ4625247

Peidong Zhang, Jin Wang, Rob Law, Xi Chen, Xian-Yong Peng, Jinxing Lin, Edmond Wu

Publication date: 22 February 2019

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.2952

zbMATH Keywords

fault diagnosisEEMDHHTBFO-GPtreelet

Mathematics Subject Classification ID

Control/observation systems involving computers (process control, etc.) (93C83) Application models in control theory (93C95) Control/observation systems in abstract spaces (93C25) Stochastic systems in control theory (general) (93E03)

Cites Work

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• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

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