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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  |  View/Download:2/0  |  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  |  View/Download:2/0  |  Submit date:2018/12/22
Autoencoder (Ae)  Classification  Extreme Learning Machines (Elm)  Fault Diagnosis  Wind Turbine  
Optimal Sensor Deployment for Manufacturing Process Monitoring Based on Quantitative Cause-Effect Graph Journal article
IEEE Transactions on Automation Science and Engineering, 2016,Volume: 13,Issue: 2,Page: 963-975
Authors:  He K.;  Jia M.;  Xu Q.
Favorite  |  View/Download:4/0  |  Submit date:2018/12/23
Condition Monitoring  Quantitative Cause-effect Graph  Sensor Deployment  Single-station Multistep Manufacturing Process  
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  |  View/Download:4/0  |  Submit date:2018/12/22
Hilbert-huang Transform  Pairwise-coupling Probabilistic Committee Machine  Simultaneous-fault Diagnosis  
Fault-tolerant control of an air heating fan using set-valued observers: An experimental evaluation Journal article
International Journal of Adaptive Control and Signal Processing, 2016,Volume: 30,Issue: 2,Page: 336-358
Authors:  Rosa P.;  Simao T.;  Silvestre C.;  Lemos J.M.
Favorite  |  View/Download:5/0  |  Submit date:2019/02/12
Fault Distinguishability  Fault Tolerant Control  Multiple-model  Set-valued Observers  
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  |  View/Download:6/0  |  Submit date:2018/12/22
Automotive Engine  Multi-signal Fusion  Probabilistic Committee Machine  Simultaneous-fault Diagnosis  Sparse Bayesian Extreme Learning Machine