Integrating adaptive input length selection strategy and unsupervised transfer learning for bearing fault diagnosis under noisy conditions-Reference-Cited by-同舟云学术

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Integrating adaptive input length selection strategy and unsupervised transfer learning for bearing fault diagnosis under noisy conditions

Published:2023-11 Issue: Volume:148 Page:110870
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Tang Guiting,Yi Cai,Liu Lei,Xing Zhan,Zhou Qiuyang,Lin Jianhui

Funder

Natural Science Foundation of Sichuan Province

Case Western Reserve University

National Natural Science Foundation of China

China Postdoctoral Science Foundation

State Key Laboratory of Traction Power

Key Research and Development Program of Sichuan Province

Publisher

Elsevier BV

Subject

Software

Reference57 articles.

1. A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders;Shao;Mech. Syst. Signal Process.,2018

2. Rolling element bearing fault diagnosis using convolutional neural network and vibration image;Hoang;Cogn. Syst. Res.,2019

3. A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning;Li;Neurocomputing,2018

4. Intelligent bearing fault diagnosis method combining compressed data acquisition and deep learning;Sun;IEEE Trans. Instrum. Meas.,2017

5. Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data;Jia;Mech. Syst. Signal Process.,2016

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1. Enhanced domain transfer deep fuzzy echo state network for rotating machinery fault diagnosis based on current signal;Applied Soft Computing;2024-11

2. Digital twin-assisted AI framework based on domain adaptation for bearing defect diagnosis in the centrifugal pump;Measurement;2024-08

3. A stable and robust fault diagnosis method for bearing using lightweight batch normalization-free residual network;Measurement Science and Technology;2024-07-15

4. A design of fuzzy rule-based classifier optimized through softmax function and information entropy;Applied Soft Computing;2024-05

5. An adaptive fully convolutional network for bearing fault diagnosis under noisy environments;Review of Scientific Instruments;2024-04-01

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