Rolling Element Bearing Fault Diagnosis by Different Data Fusion Techniques-Reference-Cited by-同舟云学术

Rolling Element Bearing Fault Diagnosis by Different Data Fusion Techniques

Published:2020-10-14 Issue: Volume: Page:341-350
ISSN:2195-4356
Container-title:Lecture Notes in Mechanical Engineering
language:
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Author:

Buchaiah Sandaram^ORCID,Shakya Piyush^ORCID

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-5701-9_28

Reference10 articles.

1. Gupta P, Pradhan MK (2017) Fault detection analysis in rolling element bearing: a review. Mater Today: Proc 4:20852094

2. Howard I (1994) A Review of rolling element bearing vibration detection, diagnosis and prognosis. DSTO Aeronautical and Maritime Research Laboratory, GPO Box 4331, October 1994

3. Jiang L, Xinxin F, Jianguo C, Zhonghai F (2012) Fault detection of rolling element bearing based on principal component analysis. In: 24th Chinese control and decision conference (CCDC)

4. Shakya P, Kulkarni MS, Darpe AK (2015) Bearing diagnosis based on Mahalanobis–Taguchi–Gram–Schmidt method. J Sound Vib 337:342–362

5. Soylemezoglu A, Jagannathan S, Saygin C (2010) Mahalanobis Taguchi System (MTS) as Prognostics tool for rolling element bearing failure. J Manuf Sci Eng 132:051014-1

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