Fault anomaly detection method of aero-engine rolling bearing based on distillation learning-Reference-Cited by-同舟云学术

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Fault anomaly detection method of aero-engine rolling bearing based on distillation learning

Published:2023-11 Issue: Volume: Page:
ISSN:0019-0578
Container-title:ISA Transactions
language:en
Short-container-title:ISA Transactions

Author:

Kang Yuxiang,Chen Guo,Wang Hao,Sheng Jiajiu,Wei Xunkai

Funder

National Natural Science Foundation of China

National Major Science and Technology Projects of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation

Reference30 articles.

1. Aeroengine Prediction And Health Management;Xunkai,2014

2. Applications of machine learning to machine fault diagnosis: a review and roadmap (Invited Review Paper);Lei;Mech Syst Signal Process,2020

3. Online fault diagnosis method based on transfer convolutional neural networks;Xu;IEEE Trans Instrum Meas,2019

4. Unsupervised domain-share CNN for machine fault transfer diagnosis from steady speeds to time-varying speeds;CAO;J Manuf Syst,2022

5. Electric locomotive bearing fault diagnosis using a novel convolutional deep belief network;SHAO;IEEE Trans Ind Electron,2018

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1. Encoder signal-based optimized Savitzky-Golay and adaptive spectrum editing for feature extraction of rolling element bearing under low-speed and variable-speed conditions;ISA Transactions;2024-08

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