Automatic Fault Diagnosis of Drills Using Artificial Neural Networks-Reference-Cited by-同舟云学术

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Automatic Fault Diagnosis of Drills Using Artificial Neural Networks

Published:2017-12 Issue: Volume: Page:
ISSN:
Container-title:2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)
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Author:

Vununu Caleb,Kwon Ki-Ryong,Lee Eung-Joo,Moon Kwang-Seok,Lee Suk-Hwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8258911/8260597/08260769.pdf?arnumber=8260769

Cited by 8 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. MPNet: A lightweight fault diagnosis network for rotating machinery;Measurement;2025-01

2. A survey of mechanical fault diagnosis based on audio signal analysis;Measurement;2023-10

3. Intelligent Machinery Fault Diagnosis Method Based on Adaptive Deep Convolutional Neural Network: Using Dental Milling Cutter Malfunction Classifications as an Example;Applied Sciences;2023-06-30

4. Application of Neural Networks in Autonomous Driving Vehicles to Enhance Controllability of Lateral Tip-Over Stability Hazards;Communications in Computer and Information Science;2022

5. End-to-End Deep Learning by MCU Implementation: An Intelligent Gripper for Shape Identification;Sensors;2021-01-28

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