An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault dia...

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Bibliographic Details
Main Authors: Shaobo Li, Guokai Liu, Xianghong Tang, Jianguang Lu, Jianjun Hu
Format: Article
Language:English
Published: MDPI AG 2017-07-01
Series:Sensors
Subjects:
bearing fault diagnosis
D-S evidence theory
convolutional neural networks
deep learning
Online Access:https://www.mdpi.com/1424-8220/17/8/1729

Internet

https://www.mdpi.com/1424-8220/17/8/1729

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