An Adaptive Weighted Multiscale Convolutional Neural Network for Rotating Machinery Fault Diagnosis Under Variable Operating Conditions

An Adaptive Weighted Multiscale Convolutional Neural Network for Rotating Machinery Fault Diagnosis Under Variable Operating Conditions

Extracting robust fault sensitive features of vibration signals remains a challenge for rotating machinery fault diagnosis under variable operating conditions. Most existing fault diagnosis methods based on the convolutional neural network (CNN) can only extract single-scale features, which not only...

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Bibliographic Details
Main Authors: Huihui Qiao, Taiyong Wang, Peng Wang, Lan Zhang, Mingda Xu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Adaptive weighted multiscale feature learning
convolutional neural network
deep learning
fault diagnosis
rotating machinery
variable operating conditions
Online Access:https://ieeexplore.ieee.org/document/8808927/

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