Enhancing Cutting Sound Quality in Tool Wear Monitoring via Hybrid Domain Loss UNet Network-Reference-Cited by-同舟云学术

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Enhancing Cutting Sound Quality in Tool Wear Monitoring via Hybrid Domain Loss UNet Network

Published:2024-07-02 Issue: Volume: Page:2266-2271
ISSN:
Container-title:2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC)
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Author:

Chen Jian Wen¹,Tsai Meng Shiun²,Hung Che Lun³

Affiliation:

1. National Tsing Hua University,Department of Computer Science,Hsinchu,Taiwan

2. National Taiwan University,Department of Mechanical Engineering,Taipei,Taiwan

3. Institute of Biomedical Informatics, National Yang Ming Chiao Tung University,Taipei,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10633276/10633246/10633426.pdf?arnumber=10633426

Reference16 articles.

1. Investigation of microstructure, mechanical and machinability properties of Mo-added steel produced by powder metallurgy method

2. Tool wear monitoring in micromilling using Support Vector Machine with vibration and sound sensors

3. Estimation of tool wear during CNC milling using neural network-based sensor fusion

4. An overview of data acquisition system for cutting force measuring and optimization in milling

5. Tool failure detection method for high-speed milling using vibration signal and reconfigurable bandpass digital filtering

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