Integrated model of BP neural network and CNN algorithm for automatic wear debris classification-Reference-Cited by-同舟云学术

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Integrated model of BP neural network and CNN algorithm for automatic wear debris classification

Published:2019-04 Issue: Volume:426-427 Page:1761-1770
ISSN:0043-1648
Container-title:Wear
language:en
Short-container-title:Wear

Author:

Wang S.,Wu T.H.,Shao T.,Peng Z.X.

Funder

National Natural Science Foundation of China

International Collaborative Plan of Shaanxi Province

NSFC-Zhejiang Joint Fund

K. C. Wang Education Foundation

Publisher

Elsevier BV

Subject

Materials Chemistry,Surfaces, Coatings and Films,Surfaces and Interfaces,Mechanics of Materials,Condensed Matter Physics

Reference32 articles.

1. Wear mechanisms and surface topography of artificial hip joint components at the subsequent stages of tribological tests;Niemczewska-Wójcik;Measurement,2017

2. Modeling wear state evolution using real time wear debris features;Wang;Tribol. Trans.,2017

3. Advancement and current status of wear debris analysis for machine condition monitoring: a review;Kumar;Ind. Lubr. Tribol.,2013

4. Wear particle analysis — utilization of quantitative computer image analysis: a review;Raadnui;Tribol. Int.,2005

5. Self organizing analysis platform for wear particle;Memon;Int. J. Comput. Electr. Autom. Control Inf. Eng.,2007

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