Intelligent prediction of wear location and mechanism using image identification based on improved Faster R-CNN model-Reference-Cited by-同舟云学术

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Intelligent prediction of wear location and mechanism using image identification based on improved Faster R-CNN model

Published:2022-05 Issue: Volume:169 Page:107466
ISSN:0301-679X
Container-title:Tribology International
language:en
Short-container-title:Tribology International

Author:

Wang Miao,Yang Lei,Zhao Zhibin,Guo Yanjie

Funder

National Major Science and Technology Projects of China

Fundamental Research Funds for the Central Universities

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

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

Reference41 articles.

1. Research on financing efficiency and influencing factors of equipment manufacturing industry-regression model based on SFA panel data;Wang;J Intell Fuzzy Syst,2021

2. A review on detection technology of mechanical wear;Peng;Lubr Eng,2018

3. Comparison of lubricant analytic techniques for mechanical wear condition monitoring, gas turbine;Huo;Technology,2001

4. Reliable fault diagnosis for low-speed bearings using individually trained support vector machines with kernel discriminative feature analysis;Kang;IEEE Trans Power Electron,2015

5. Machine learning based anomaly detection and classification of acoustic emission events for wear monitoring in sliding bearing systems;Konig;Tribol Int,2021

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