Wear particle classification using genetic programming evolved features-Reference-Cited by-同舟云学术

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Wear particle classification using genetic programming evolved features

Published:2018-01-10 Issue:5 Volume:30 Page:229-246
ISSN:0954-0075
Container-title:Lubrication Science
language:en
Short-container-title:Lubr. Sci.

Author:

Xu Bin¹^ORCID,Wen Guangrui¹²³,Zhang Zhifen¹^ORCID,Chen Feng¹

Affiliation:

1. School of Mechanical Engineering; Xi'an Jiaotong University; Xi'an Shaanxi 710049 China

2. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System; Xi'an Jiaotong University; Xi'an Shaanxi 710049 China

3. School of Mechanical Engineering; Xinjiang University; Wulumuqi 830047 China

Funder

National Natural Science Foundation of China

Equipment Pre-research Sharing Technology and Domain Funds

National Key Research and Development Project

Publisher

Wiley

Subject

Materials Chemistry,Surfaces, Coatings and Films

Reference32 articles.

1. Study of grey relational grade identification for ferrography based on characteristic analysis of wear debris;Hu;Tribotest,2004

2. A wear particle identification method by combining principal component analysis and grey relational analysis;Wang;Wear,2013

3. Ferrography-then and now;Roylance;Tribology International,2005

4. Feature generation using genetic programming with application to fault classification;Guo;IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics,2005

5. Condition monitoring of industrial machinery through lubricant oil analysis;Leão;Tribotest,1996

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