Automatic Classification of Rotating Machinery Defects Using Machine Learning (ML) Algorithms-Reference-Cited by-同舟云学术

Automatic Classification of Rotating Machinery Defects Using Machine Learning (ML) Algorithms

Published:2020-05-30 Issue: Volume: Page:193-203
ISSN:2190-3018
Container-title:Human Centred Intelligent Systems
language:
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Author:

Zoungrana Wend-Benedo,Chehri Abdellah^ORCID,Zimmermann Alfred

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-5784-2_16

Reference17 articles.

1. Nembhard, A.D., Sinha, J.K., Elbhbah, K., Pinkerton, A.J.: Fault diagnosis of rotating machines using vibration and bearing temperature measurements. Diagnostyka 14(3), 45–52 (2013)

2. Tabaszewski, M.: Optimization of a nearest neighbours classifier for diagnosis of condition of rolling bearings. Diagnostyka 15(1), 37–42 (2014)

3. Astolfi, D., Castellani, F., Terzi, L.: Fault prevention and diagnosis through SCADA temperature data analysis of an onshore wind farm. Diagnostyka 15, 71–78 (2014)

4. Lecture Notes of the Institute for Computer Sciences, Smart Innovation Systems and Technologies;A Chehri,2019

5. Lecture Notes of the Institute for Computer Sciences, Smart Innovation Systems and Technologies;A Chehri,2019

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