Construction of hierarchical diagnosis network based on deep learning and its application in the fault pattern recognition of rolling element bearings-Reference-Cited by-同舟云学术

Construction of hierarchical diagnosis network based on deep learning and its application in the fault pattern recognition of rolling element bearings

Published:2016-05 Issue: Volume:72-73 Page:92-104
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Gan Meng,Wang Cong,Zhu Chang׳an

Funder

National Key Basic Research Program of China

Key Technologies R&D Program of Anhui Province

Publisher

Elsevier BV

Subject

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

Reference32 articles.

1. Evaluation of principal component analysis and neural network performance for bearing fault diagnosis from vibration signal processed by RS and DF analyses;de Moura;Mech. Syst. Signal Process.,2011

2. Multi-fault diagnosis for rolling element bearings based on ensemble empirical mode decomposition and optimized support vector machines;Zhang;Mech. Syst. Signal Process.,2013

3. Automated diagnosis of rolling bearings using MRA and neural networks;Castejon;Mech. Syst. Signal Process.,2010

4. An intelligent fault identification method of rolling bearings based on LSSVM optimized by improved PSO;Xu;Mech. Syst. Signal Process.,2013

5. Support vector machine in machine condition monitoring and fault diagnosis;Widodo;Mech. Syst. Signal Process.,2007

Cited by 447 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Acoustic emission monitoring for damage diagnosis in composite laminates based on deep learning with attention mechanism;Mechanical Systems and Signal Processing;2025-01

2. A fault diagnosis method for hydraulic system based on multi-branch neural networks;Engineering Applications of Artificial Intelligence;2024-11

3. Fault Detection of Rotating Machines Using poly-Coherent Composite Spectrum of Measured Vibration Responses with Machine Learning;Machines;2024-08-19

4. A survey on fault diagnosis of rotating machinery based on machine learning;Measurement Science and Technology;2024-07-29

5. Rolling bearing fault diagnosis method based on PE-DCM and ViT;Measurement Science and Technology;2024-07-11