Supervised-Learning-Based Intelligent Fault Diagnosis for Mechanical Equipment-Reference-Cited by-同舟云学术

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Supervised-Learning-Based Intelligent Fault Diagnosis for Mechanical Equipment

Published:2021 Issue: Volume:9 Page:116147-116162
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hong Geonkyo,Suh Dongjun

Funder

National Research Foundation of Korea

Korea government

High Performance Computing (HPC) Support Project, supported by the MSIT and the National IT Industry Promotion Agency

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09511427.pdf?arnumber=9511427

Cited by 9 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

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2. Anomalous sound detection for machine condition monitoring using 3D tensor representation of sound and 3D deep convolutional neural network;Multimedia Tools and Applications;2023-10-17

3. Mel Spectrogram-based advanced deep temporal clustering model with unsupervised data for fault diagnosis;Expert Systems with Applications;2023-05

4. Unsupervised Remaining Useful Life Prediction for Bearings with Virtual Health Index;2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE);2023-02-25

5. Robust and Lightweight Deep Learning Model for Industrial Fault Diagnosis in Low-Quality and Noisy Data;Electronics;2023-01-13

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