articleTop 1% cited
A novel deep learning method based on attention mechanism for bearing remaining useful life prediction
Applied Soft Computing · 2019 · Vol. 86 · pp. 105919–105919
Yuanhang Chen(Harbin Institute of Technology)Gaoliang Peng✉(Harbin Institute of Technology)Zhiyu Zhu(Harbin Institute of Technology)Sijue Li(Harbin Institute of Technology)
Machine Fault Diagnosis TechniquesGear and Bearing Dynamics AnalysisMechanical Failure Analysis and SimulationComputer scienceBearing (navigation)Artificial intelligenceConstruct (python library)Artificial neural networkSet (abstract data type)Rotation (mathematics)Data miningData setMechanism (biology)
Funding
- National Natural Science Foundation of China
Citations
370
FWCI
27.07
field-weighted impact
References
55
Percentile
100%
vs. same field & year
Citations per year
References
Learning representations by back-propagating errors
Nature · 1986 · 30,045 citations
Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network
Mechanical Systems and Signal Processing · 2014 · 495 citations
Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods
Mechanical Systems and Signal Processing · 2006 · 510 citations
Remaining useful life estimation – A review on the statistical data driven approaches
European Journal of Operational Research · 2010 · 1,989 citations
Long Short-Term Memory
Neural Computation · 1997 · 95,078 citations
Prognosis of Defect Propagation Based on Recurrent Neural Networks
IEEE Transactions on Instrumentation and Measurement · 2011 · 304 citations
Learning long-term dependencies with gradient descent is difficult
IEEE Transactions on Neural Networks · 1994 · 8,303 citations
ImageNet classification with deep convolutional neural networks
Communications of the ACM · 2017 · 75,550 citations
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