A new intelligent fault diagnosis method for bearing in different speeds based on the FDAF-score algorithm, binary particle swarm optimization, and support vector machine-Reference-Cited by-同舟云学术

A new intelligent fault diagnosis method for bearing in different speeds based on the FDAF-score algorithm, binary particle swarm optimization, and support vector machine

Published:2019-11-11 Issue:13 Volume:24 Page:10005-10023
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Nezamivand Chegini Saeed^ORCID,Bagheri Ahmad,Najafi Farid

Funder

University og Guilan

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-019-04516-z.pdf

Reference49 articles.

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2. Attoui I, Fergani N, Boutasseta N, Oudjani B, Deliou A (2017) A new time–frequency method for identification and classification of ball bearing faults. J Sound Vib 397:241–265. https://doi.org/10.1016/j.jsv.2017.02.041

3. Banka H, Dara S (2015) A Hamming distance based binary particle swarm optimization (HDBPSO) algorithm for high dimensional feature selection, classification and validation. Pattern Recognit Lett 52:94–100. https://doi.org/10.1016/j.patrec.2014.10.007

4. Bearing Data Center (2016) Case Western Reserve University. http://csegroups.case.edu/bearingdatacenter/home

5. Bhuyan HK, Kamila NK (2015) Privacy preserving sub-feature selection in distributed data mining. Appl Soft Comput 36:552–569. https://doi.org/10.1016/j.asoc.2015.06.060

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