Rolling element bearing fault feature extraction using an optimal chirplet-Reference-Cited by-同舟云学术

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Rolling element bearing fault feature extraction using an optimal chirplet

Published:2018-09-06 Issue:10 Volume:29 Page:105004
ISSN:0957-0233
Container-title:Measurement Science and Technology
language:
Short-container-title:Meas. Sci. Technol.

Author:

Jiang Hongkai^ORCID,Lin Ying,Meng Zhiyong

Funder

National Natural Science Foundation of China

Seed Foundation of Innovation and Creation for Graduate Students in Northwestern Polytechnical University

The Aviation Science Foundation of China

Publisher

IOP Publishing

Subject

Applied Mathematics,Instrumentation,Engineering (miscellaneous)

Link

http://iopscience.iop.org/article/10.1088/1361-6501/aad8e8/pdf

Reference44 articles.

1. Automatic fault feature extraction of mechanical anomaly on induction motor bearing using ensemble super-wavelet transform

2. EEMD method and WNN for fault diagnosis of locomotive roller bearings

3. Multiwavelet transform and its applications in mechanical fault diagnosis – A review

4. Gearbox fault diagnosis using adaptive redundant Lifting Scheme

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1. First-order differential filtering spectrum division method and information fusion multi-scale network for fault diagnosis of bearings under different loads;Measurement Science and Technology;2022-04-27

2. Rolling bearing fault feature detection using nonconvex wavelet total variation;Measurement;2021-07

3. Rolling bearing fault feature extraction using Adaptive Resonance-based Sparse Signal Decomposition;Engineering Research Express;2021-01-15

4. Financial accounting intelligence management of internet of things enterprises based on data mining algorithm;Journal of Intelligent & Fuzzy Systems;2019-11-22

5. An optimal variational mode decomposition for rolling bearing fault feature extraction;Measurement Science and Technology;2019-04-10

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