Fault diagnosis of rotating machinery based on dual convolutional-capsule network (DC-CN)-Reference-Cited by-同舟云学术

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Fault diagnosis of rotating machinery based on dual convolutional-capsule network (DC-CN)

Published:2022-01 Issue: Volume:187 Page:110258
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Li DeCai,Zhang Mian,Kang TianBo,Li Bin,Xiang HongBiao,Wang KeSheng,Pei ZhenLong,Tang XiuYang,Wang Peng

Funder

Natural Science Foundation of Tianjin Science and Technology Correspondent Project

National Natural Science Foundation of China

University of Electronic Science and Technology of China

Natural Science Foundation of Tianjin City

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference38 articles.

1. Artificial intelligence for fault diagnosis of rotating machinery: A review;Liu;Mech. Syst. Signal Process.,2018

2. Vibrations for fault detection in electric machines;Ugwiri;IEEE Instrum. Measur. Mag.,2020

3. A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings;Liu;Measurement,2020

4. Tooth faults detection of planetary gearboxes based on tooth root strain signal of ring gear;Zhang;Measurement,2021

5. Maintenance Engineering Handbook;Higgis,2002

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