Bearing Damage Detection With Orthogonal and Nonnegative Low-Rank Feature Extraction-Reference-Cited by-同舟云学术

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Bearing Damage Detection With Orthogonal and Nonnegative Low-Rank Feature Extraction

Published:2024-02 Issue:2 Volume:20 Page:2944-2955
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Gabor Mateusz¹^ORCID,Zdunek Rafal¹^ORCID,Zimroz Radoslaw²^ORCID,Wylomanska Agnieszka³^ORCID

Affiliation:

1. Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, Wroclaw, Poland

2. Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Wroclaw, Poland

3. Faculty of Pure and Applied Mathematics, Wroclaw University of Science and Technology, Wroclaw, Poland

Funder

National Center of Science

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/10411967/10213276.pdf?arnumber=10213276

Reference35 articles.

1. Recent advances in time–frequency analysis methods for machinery fault diagnosis: A review with application examples

2. Short term spectral analysis, synthesis, and modification by discrete Fourier transform

3. Rolling element bearing diagnostics—A tutorial

4. Informative frequency band selection in the presence of non-Gaussian noise – a novel approach based on the conditional variance statistic with application to bearing fault diagnosis

5. Proportional selection scheme: A frequency band division tool for rolling element bearing diagnostics

Cited by 3 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. Optimal filter design using mountain gazelle optimizer driven by novel sparsity index and its application to fault diagnosis;Applied Acoustics;2024-11

2. Local damage detection in rolling element bearings based on a single ensemble empirical mode decomposition;Knowledge-Based Systems;2024-10

3. Robust coherent and incoherent statistics for detection of hidden periodicity in models with non-Gaussian additive noise;EURASIP Journal on Advances in Signal Processing;2024-06-25

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