An Intelligent System for Grinding Wheel Condition Monitoring Based on Machining Sound and Deep Learning-Reference-Cited by-同舟云学术

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An Intelligent System for Grinding Wheel Condition Monitoring Based on Machining Sound and Deep Learning

Published:2020 Issue: Volume:8 Page:58279-58289
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Lee Cheng-Hsiung^ORCID,Jwo Jung-Sing,Hsieh Han-Yi,Lin Ching-Sheng

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09044813.pdf?arnumber=9044813

Cited by 56 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. Research progress on intelligent monitoring of tool condition based on deep learning;The International Journal of Advanced Manufacturing Technology;2024-08-20

2. Precision forecasting of grinding wheel Wear: A TransBiGRU model for advanced industrial predictive maintenance;Measurement;2024-07

3. Condition monitoring of grinding wheels: Potential of internal control signals;Production Engineering;2024-06-20

4. The Vibration Spectrograms as well as EL System for Assessing the Cutting Tool and Insert Condition;2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2024-05-14

5. Design of elements of specialized technological equipment for finishing processing of parts;IOP Conference Series: Earth and Environmental Science;2024-05-01

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