A New Deep Stacked Architecture for Multi-Fault Machinery Identification With Imbalanced Samples

A New Deep Stacked Architecture for Multi-Fault Machinery Identification With Imbalanced Samples

Effective intelligent fault diagnosis of rotating machinery using its vibrational signals has a considerable influence on certain analysis factors such as the reliability, performance, and productivity of a variety of modern manufacturing machines. Traditional intelligent approaches lack generalizat...

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Bibliographic Details
Main Authors: Hanen Karamti, Maha M. A. Lashin, Fadwa M. Alrowais, Abeer M. Mahmoud
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Fault diagnosis
imbalanced samples
logistic regression
rotating machinery
sparse autoencoders
variational autoencoder
Online Access:https://ieeexplore.ieee.org/document/9399084/

Internet

https://ieeexplore.ieee.org/document/9399084/

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