Morphological Feature Extraction Based on Multiview Images for Wear Debris Analysis in On-line Fluid Monitoring-Reference-Cited by-同舟云学术

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Morphological Feature Extraction Based on Multiview Images for Wear Debris Analysis in On-line Fluid Monitoring

Published:2016-08-10 Issue:3 Volume:60 Page:408-418
ISSN:1040-2004
Container-title:Tribology Transactions
language:en
Short-container-title:Tribology Transactions

Author:

Wu Tonghai,Peng Yeping,Wang Shuo,Chen Feng,Kwok Ngaiming,Peng Zhongxiao

Publisher

Informa UK Limited

Subject

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

Link

https://www.tandfonline.com/doi/pdf/10.1080/10402004.2016.1174325

Reference39 articles.

1. Advancement and current status of wear debris analysis for machine condition monitoring: a review

2. Description of Wear Debris from On-Line Ferrograph Images by Their Statistical Color

3. A wear particle identification method by combining principal component analysis and grey relational analysis

4. Engine Wear Monitoring with OLVF

Cited by 22 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. Probability-weighted ensemble support vector machine for intelligent recognition of moving wear debris from joint implant;Tribology International;2023-08

2. Online Wear Particle Detection Sensors for Wear Monitoring of Mechanical Equipment—A Review;IEEE Sensors Journal;2022-02-15

3. An object detection network for wear debris recognition in ferrography images;Journal of the Brazilian Society of Mechanical Sciences and Engineering;2022-01-31

4. Research on 3D reconstruction method of wear particle dynamic image based on multi contour space mapping;IOP Conference Series: Materials Science and Engineering;2021-11-01

5. Three-dimensional reconstruction of wear particles by multi-view contour fitting and dense point-cloud interpolation;Measurement;2021-08

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