Adaptive artificial intelligence for automatic identification of defect in the angular contact bearing-Reference-Cited by-同舟云学术

Adaptive artificial intelligence for automatic identification of defect in the angular contact bearing

Published:2017-06-24 Issue:8 Volume:29 Page:277-287
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Kumar Anil^ORCID,Kumar Rajesh^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/article/10.1007/s00521-017-3123-4/fulltext.html

Reference25 articles.

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2. Borghesani P, Pennacchi P, Chatterton S (2014) The relationship between Kurtosis- and envelope-based indexes for the diagnostic of rolling element bearings. Mech Syst Signal Process 43:25–43

3. Yang Y, Yu DJ, Cheng JS (2006) A roller bearing fault diagnosis method based on EMD energy entropy and ANN. J Sound Vib 294:269–277

4. Hu C, Peng Z (2016) Frequency band selection based on the kurtosis of the squared envelope spectrum and its application in bearing fault diagnosis. Proc IMechE Part C J Mech Eng Sci. doi: 10.1177/0954406215595655

5. Wang H, Chen J, Dong G (2014) Fault diagnosis of rolling bearing’s early weak fault based on minimum entropy de-convolution and fast Kurtogram algorithm. Proc IMechE Part C J Mech Eng Sci. doi: 10.1177/0954406214564692

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