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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 ChenGaoliang PengZhiyu ZhuSijue Li
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
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100%
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References
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Nature · 1986 · 30,045 citations
Remaining useful life estimation – A review on the statistical data driven approaches
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Long Short-Term Memory
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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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