Blade Rub-Impact Fault Identification Using Autoencoder-Based Nonlinear Function Approximation and a Deep Neural Network

Blade Rub-Impact Fault Identification Using Autoencoder-Based Nonlinear Function Approximation and a Deep Neural Network

A blade rub-impact fault is one of the complex and frequently appearing faults in turbines. Due to their nonlinear and nonstationary nature, complex signal analysis techniques, which are expensive in terms of computation time, are required to extract valuable fault information from the vibration sig...

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Bibliographic Details
Main Authors: Alexander E. Prosvirin, Farzin Piltan, Jong-Myon Kim
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
data-driven fault diagnosis
deep autoencoder
deep neural network
deep learning-based function approximation
fault diagnosis
rotating machinery
Online Access:https://www.mdpi.com/1424-8220/20/21/6265

Internet

https://www.mdpi.com/1424-8220/20/21/6265

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