Fault Classification of Low-Speed Bearings Based on Support Vector Machine for Regression and Genetic Algorithms Using Acoustic Emission-Reference-Cited by-同舟云学术

Fault Classification of Low-Speed Bearings Based on Support Vector Machine for Regression and Genetic Algorithms Using Acoustic Emission

Published:2019-06-12 Issue:5 Volume:7 Page:455-464
ISSN:2523-3920
Container-title:Journal of Vibration Engineering & Technologies
language:en
Short-container-title:J. Vib. Eng. Technol.

Author:

Omoregbee Henry Ogbemudia,Heyns P. Stephan

Publisher

Springer Science and Business Media LLC

Link

http://link.springer.com/content/pdf/10.1007/s42417-019-00143-y.pdf

Reference26 articles.

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3. Achmad W, Eric YK, Jong-Duk S, Bo-Suk Y, Andy CCT, Dong-Sik G, Byeong-Keun C, Joseph M (2009) Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine, Elsevier. Expert Syst Appl 36:7252–7261

4. Changqing S, Dong W, Yongbin L, Fanrang K, Peter WT (2014) Recognition of rolling bearing fault patterns and sizes based on two-layer support vector regression machines. Smart Struct Syst 13(3):453–471

5. Yu Y, Dejie Y, Junsheng C (2006) A fault diagnosis approach for roller bearing based on IMF envelope spectrum and SVM. Elsevier (ScienceDirect) Meas 40:943–950

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