Application of a coarse-to-fine minimum entropy deconvolution method for rotating machines fault detection-Reference-Cited by-同舟云学术

Application of a coarse-to-fine minimum entropy deconvolution method for rotating machines fault detection

Published:2023-09 Issue: Volume:198 Page:110431
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Miao Yonghao^ORCID,Li Chenhui,Zhang Boyao,Lin Jing

Publisher

Elsevier BV

Subject

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

Reference37 articles.

1. Rolling element bearing diagnostics—A tutorial;Randall;Mech. Syst. Sig. Process.,2011

2. Condition monitoring and fault diagnosis of planetary gearboxes: A review;Lei;Measurement,2014

3. Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art;Riera-Guasp;IEEE T Ind. Electron,2015

4. Gearbox condition monitoring in wind turbines: A review;Salameh;Mech. Syst. Signal Process.,2018

5. Feature Mode Decomposition: New Decomposition Theory for Rotating Machinery Fault Diagnosis;Miao;IEEE Trans. Ind. Electron.,2023

Cited by 19 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. Optimization of spectral kurtosis-based filtering through flow direction algorithm for early fault detection;Measurement;2025-02

2. Cyclostationarity blind deconvolution via eigenvector screening and its applications to the condition monitoring of rotating machinery;Mechanical Systems and Signal Processing;2025-01

3. Simulation-driven unsupervised fault diagnosis of rolling bearing under time-varying speeds;Structural Health Monitoring;2024-08-20

4. Period enhanced feature mode decomposition and its application for bearing weak fault feature extraction;Measurement Science and Technology;2024-08-14

5. Resilient fast nonlinear blind deconvolution with uniform initialization for the bearing fault diagnosis;Structural Health Monitoring;2024-08-08