A CEEMDAN-Assisted Deep Learning Model for the RUL Estimation of Solenoid Pumps

A CEEMDAN-Assisted Deep Learning Model for the RUL Estimation of Solenoid Pumps

This paper develops a data-driven remaining useful life prediction model for solenoid pumps. The model extracts high-level features using stacked autoencoders from decomposed pressure signals (using complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm). These h...

Full description

Bibliographic Details
Main Authors: Ugochukwu Ejike Akpudo, Jang-Wook Hur
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Electronics
Subjects:
empirical mode decomposition
CEEMDAN
deep feature learning
stacked autoencoders
gated recurrent units
remaining useful life estimation
Online Access:https://www.mdpi.com/2079-9292/10/17/2054

Internet

https://www.mdpi.com/2079-9292/10/17/2054

Similar Items