Tool Wear Prediction with External Signals Based on Lightweight Deep Learning Model-Reference-Cited by-同舟云学术

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Tool Wear Prediction with External Signals Based on Lightweight Deep Learning Model

Published:2020-11-06 Issue: Volume: Page:
ISSN:
Container-title:2020 Chinese Automation Congress (CAC)
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Author:

Zheng Liyang,Jiang Yuan,Zhang Yu,Guo Jincheng

Funder

Huazhong University of Science and Technology

National Natural Science Foundation of China

State Key Laboratory of Industrial Control Technology

Zhejiang University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9326315/9326464/09327649.pdf?arnumber=9327649

Cited by 2 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. Artificial Intelligence techniques and Internet of things sensors for tool condition monitoring in milling: A review;Materials Research Proceedings;2024-05-15

2. Multiple Activation Functions and Data Augmentation-Based Lightweight Network for In Situ Tool Condition Monitoring;IEEE Transactions on Industrial Electronics;2022-12

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