Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization

被引：0
|
作者：
Umar, Muhammad [1 ]
Siddique, Muhammad Farooq [1 ]
Ullah, Niamat [1 ]
Kim, Jong-Myon [1 ,2 ]
机构：
[1] Department of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan,44610, Korea, Republic of
[2] PD Technology Co., Ltd., Ulsan,44610, Korea, Republic of
来源：
Applied Sciences (Switzerland) | 2024年 / 14卷 / 22期
基金：
新加坡国家研究基金会;
关键词：
Acoustic emission testing - Bearings (machine parts) - Fracture mechanics - Gear cutting machines - Multilayer neural networks - Shafts (machine components) - Wavelet transforms;
D O I：
10.3390/app142210404
中图分类号：
学科分类号：
摘要：
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