A fault diagnosis method for hydraulic system based on multi-branch neural networks-Reference-Cited by-同舟云学术

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A fault diagnosis method for hydraulic system based on multi-branch neural networks

Published:2024-11 Issue: Volume:137 Page:109188
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Liu Huizhou^ORCID,Yan Shibo,Huang Mengxing,Huang Zhong

Funder

Hainan University

Publisher

Elsevier BV

Reference41 articles.

1. Fault diagnosis of HTS-SLIM based on 3D finite element method and hilbert-huang transform;Ahmadpour;IEEE Access,2022

2. Data-driven Fault Diagnosis in a complex hydraulic system based on early classification;Askari;IFAC-PapersOnLine,2022

3. A data-driven early micro-leakage detection and localization approach of hydraulic systems;Cai;J. Cent. S. Univ.,2021

4. Assoc comp M. XGBoost: a scalable tree boosting system;Chen,2016

5. Detecting of transient vibration signatures using an improved fast spatial-spectral ensemble kurtosis kurtogram and its applications to mechanical signature analysis of short duration data from rotating machinery;Chen;Mech. Syst. Signal Process.,2013

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