An improved method for restraining the end effect in empirical mode decomposition and its applications to the fault diagnosis of large rotating machinery-Reference-Cited by-同舟云学术

An improved method for restraining the end effect in empirical mode decomposition and its applications to the fault diagnosis of large rotating machinery

Published:2008-07 Issue:3-5 Volume:314 Page:586-602
ISSN:0022-460X
Container-title:Journal of Sound and Vibration
language:en
Short-container-title:Journal of Sound and Vibration

Author:

Wu Fangji,Qu Liangsheng

Publisher

Elsevier BV

Subject

Mechanical Engineering,Mechanics of Materials,Acoustics and Ultrasonics,Condensed Matter Physics

Reference14 articles.

1. Empirical mode decomposition in 2-D space and time: a tool for space–time rainfall analysis and nowcasting;Sinclair;Hydrology and Earth System Sciences Discussions,2005

2. A roller bearing fault diagnosis method based on EMD energy entropy and ANN;Yang;Journal of Sound and Vibration,2006

3. Introduction to the Hilbert–Huang transform and its related mathematical problems;Huang;Interdisciplinary Mathematics,2005

4. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis;Huang;Proceedings of the Royal Society of London Series A,1998

5. The processing of end effects in EMD method by autoregressive model;Zhang;Progresses in Nature Science,2003

Cited by 80 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. An improved empirical mode decomposition method with ensemble classifiers for analysis of multichannel EEG in BCI emotion recognition;Computer Methods in Biomechanics and Biomedical Engineering;2024-06-26

2. A short-term wind speed prediction method utilizing rolling decomposition and time-series extension to avoid information leakage;Energy Sources, Part A: Recovery, Utilization, and Environmental Effects;2024-02-28

3. Extraction of periodic signals in Global Navigation Satellite System (GNSS) vertical coordinate time series using the adaptive ensemble empirical modal decomposition method;Nonlinear Processes in Geophysics;2024-02-21

4. Prediction of wool fibre breaking strength based on acoustic emission signal parameters and combined noise reduction method;Nondestructive Testing and Evaluation;2024-01-29

5. Package AdvEMDpy: Algorithmic variations of empirical mode decomposition in Python;Annals of Actuarial Science;2023-05-05