Rolling Bearing Fault Prediction Method Based on QPSO-BP Neural Network and Dempster–Shafer Evidence Theory

Rolling Bearing Fault Prediction Method Based on QPSO-BP Neural Network and Dempster–Shafer Evidence Theory

To effectively predict the rolling bearing fault under different working conditions, a rolling bearing fault prediction method based on quantum particle swarm optimization (QPSO) backpropagation (BP) neural network and Dempster−Shafer evidence theory is proposed. First, the original vibrat...

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Bibliographic Details
Main Authors: Lanjun Wan, Hongyang Li, Yiwei Chen, Changyun Li
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Energies
Subjects:
rolling bearing
fault prediction
quantum particle swarm optimization
backpropagation neural network
dempster–shafer evidence theory
Online Access:https://www.mdpi.com/1996-1073/13/5/1094

Internet

https://www.mdpi.com/1996-1073/13/5/1094

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