A hybrid convolutional neural network for intelligent wear particle classification-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A hybrid convolutional neural network for intelligent wear particle classification

Published:2019-10 Issue: Volume:138 Page:166-173
ISSN:0301-679X
Container-title:Tribology International
language:en
Short-container-title:Tribology International

Author:

Peng Yeping,Cai Junhao,Wu Tonghai,Cao Guangzhong,Kwok Ngaiming,Zhou Shengxi,Peng Zhongxiao

Funder

Natural Science Foundation of Guangdong Province, China

Shenzhen Science and Technology Project, China

Natural Science Foundation of China

Natural Science Foundation of Shenzhen University, China

Publisher

Elsevier BV

Subject

Surfaces, Coatings and Films,Surfaces and Interfaces,Mechanical Engineering,Mechanics of Materials

Reference36 articles.

1. Prediction of wear trend of engines via on-line wear debris monitoring;Cao;Tribol Int,2018

2. Intelligent wear mode identification system for marine diesel engines based on multi-level belief rule base methodology;Yan;Meas Sci Technol,2018

3. Shape classification of wear particles by image boundary analysis using machine learning algorithms;Wei;Mech Syst Signal Process,2016

4. A hybrid search-tree discriminant technique for multivariate wear debris classification;Peng;Wear,2017

5. Automated classification of wear particles based on their surface texture and shape features;Stachowiak;Tribol Int,2008

Cited by 41 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Three-dimensional reconstruction of wear particle surfaces using multi-focus image sequence;Measurement;2024-08

2. Wear particle image analysis: feature extraction, selection and classification by deep and machine learning;Industrial Lubrication and Tribology;2024-05-21

3. Research on Ferrographic Image Fault Diagnosis Based on Channel Overlapping Technique and Information Fusion Mechanism;Journal of Tribology;2024-03-25

4. AI for tribology: Present and future;Friction;2024-03-12

5. Wear Mechanisms/Models;Materials Horizons: From Nature to Nanomaterials;2024

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3