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ELM Meets RAE-ELM: A hybrid intelligent model for multiple fault diagnosis and remaining useful life predication of rotating machinery Conference paper
Proceedings of the International Joint Conference on Neural Networks, Vancouver, BC, Canada, 24-29 July 2016
Authors:  Yang Z.-X.;  Zhang P.-B.
Favorite |  | TC[WOS]:7 TC[Scopus]:10 | Submit date:2018/12/22
Extreme Learning Machine (Elm)  Fault Diagnosis  Hybrid Intelligent Model  Network  Predication  Remaining Useful Life  
Representational learning for fault diagnosis of wind turbine equipment: A multi-layered extreme learning machines approach Journal article
Energies, 2016,Volume: 9,Issue: 6
Authors:  Yang Z.-X.;  Wang X.-B.;  Zhong J.-H.
Favorite |  | TC[WOS]:38 TC[Scopus]:58 | Submit date:2018/12/22
Autoencoder (Ae)  Classification  Extreme Learning Machines (Elm)  Fault Diagnosis  Wind Turbine  
A set-valued approach to FDI and FTC: Theory and implementation issues Conference paper
IFAC Proceedings Volumes (IFAC-PapersOnline), Mexico City, August 29-31, 2012
Authors:  P. Rosa;  P. Casau;  C. Silvestre;  S.M. Tabatabaeipour;  J. Stoustrup
Favorite |  | TC[WOS]:0 TC[Scopus]:16 | Submit date:2019/02/13
Fault Diagnosis  Fault Tolerant Control  Linear Time-varying Systems  Set-valued Observers  Uncertain Systems  
A hybrid EEMD-based SampEn and SVD for acoustic signal processing and fault diagnosis Journal article
Entropy, 2016,Volume: 18,Issue: 4
Authors:  Yang Z.-X.;  Zhong J.-H.
Favorite |  | TC[WOS]:24 TC[Scopus]:34 | Submit date:2018/12/22
Acoustic Signal Processing  Ensemble Empirical Mode Decomposition (Eemd)  Fault Diagnosis  Hybrid System  Sample Entropy (Sampen)  Singular Value Decomposition (Svd)  
Simultaneous-fault diagnosis of gearboxes using probabilistic committee machine Journal article
Sensors (Switzerland), 2016,Volume: 16,Issue: 2
Authors:  Zhong J.-H.;  Wong P.K.;  Yang Z.-X.
Favorite |  | TC[WOS]:21 TC[Scopus]:21 | Submit date:2018/12/22
Hilbert-huang Transform  Pairwise-coupling Probabilistic Committee Machine  Simultaneous-fault Diagnosis  
Sparse Bayesian extreme learning committee machine for engine simultaneous fault diagnosis Journal article
Neurocomputing, 2016,Volume: 174,Page: 331-343
Authors:  Wong P.K.;  Zhong J.;  Yang Z.;  Vong C.M.
Favorite |  | TC[WOS]:38 TC[Scopus]:47 | Submit date:2018/12/22
Automotive Engine  Multi-signal Fusion  Probabilistic Committee Machine  Simultaneous-fault Diagnosis  Sparse Bayesian Extreme Learning Machine