Multiscale attentional residual neural network framework for remaining useful life prediction of bearings

Wen Yu; Dechang Pi; Lingqiang Xie; Yi Luo

doi:10.1016/j.measurement.2021.109310

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Multiscale attentional residual neural network framework for remaining useful life prediction of bearings

Wen Yu Dechang Pi Lingqiang Xie Yi Luo

Year: 2021 Journal: Measurement Vol: 177 Pages: 109310-109310 Publisher: Elsevier BV

DOI: 10.1016/j.measurement.2021.109310

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Keywords:

Hilbert–Huang transform Residual Artificial neural network Computer science Artificial intelligence Pooling Vibration Deep learning Pattern recognition (psychology) SIGNAL (programming language) Machine learning Algorithm Computer vision

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Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Gear and Bearing Dynamics Analysis

Physical Sciences → Engineering → Mechanical Engineering

Mechanical Failure Analysis and Simulation

Physical Sciences → Engineering → Mechanical Engineering

Multiscale attentional residual neural network framework for remaining useful life prediction of bearings

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