Complex domain extension network with multi-channels information fusion for remaining useful life prediction of rotating machinery

Author:

Cao Yudong,Jia MinpingORCID,Ding Yifei,Zhao Xiaoli,Ding PengORCID,Gu Liudong

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference37 articles.

1. Machinery health prognostics: A systematic review from data acquisition to RUL prediction;Lei;Mech. Syst. Signal Process.,2018

2. Prognostics and health management design for rotary machinery systems - Reviews, methodology and applications;Lee;Mech. Syst. Signal Process.,2014

3. Modified Gaussian convolutional deep belief network and infrared thermal imaging for intelligent fault diagnosis of rotor-bearing system under time-varying speeds;Xin;Struct. Heal. Monit.,2022

4. Stationary subspaces-vector autoregressive with exogenous terms methodology for degradation trend estimation of rolling and slewing bearings;Ding;Mech. Syst. Signal Process.,2021

5. An Improved Exponential Model for Predicting Remaining Useful Life of Rolling Element Bearings;Li;IEEE Trans. Ind. Electron.,2015

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