A Novel Deep Learning Framework Based RNN-SAE for Fault Detection of Electrical Gas Generator

A Novel Deep Learning Framework Based RNN-SAE for Fault Detection of Electrical Gas Generator

The electrical generator is the key part of the electrical generation system for the oil and gas industry, and it is easy to fail, which disturbs the availability and reliability of the electrical generation in the power industry. Therefore, extracting and diagnosing the fault features from the proc...

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Bibliographic Details
Main Authors: Moath Alrifaey, Wei Hong Lim, Chun Kit Ang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep learning (DL)
fault detection
long short-term memory (LSTM)
oil and gas plant
recurrent neural networks (RNN)
stacked autoencoders (SAE)
Online Access:https://ieeexplore.ieee.org/document/9337852/

Internet

https://ieeexplore.ieee.org/document/9337852/

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