Fault Diagnosis of Rotating Machinery Using an Optimal Blind Deconvolution Method and Hybrid Invertible Neural Network

Fault Diagnosis of Rotating Machinery Using an Optimal Blind Deconvolution Method and Hybrid Invertible Neural Network

This paper proposes a novel approach to predicting the useful life of rotating machinery and making fault diagnoses using an optimal blind deconvolution and hybrid invertible neural network. First, a new optimal adaptive maximum second-order cyclostationarity blind deconvolution (OACYCBD) is develop...

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Bibliographic Details
Main Authors: Yangde Gao, Zahoor Ahmad, Jong-Myon Kim
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Sensors
Subjects:
fault diagnosis
optimal adaptive maximum second-order cyclostationarity blind deconvolution
health index
hybrid invertible neural network
Online Access:https://www.mdpi.com/1424-8220/24/1/256

Internet

https://www.mdpi.com/1424-8220/24/1/256

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