Multi-sensor data fusion-enabled semi-supervised optimal temperature-guided PCL framework for machinery fault diagnosis-Reference-Cited by-同舟云学术

Multi-sensor data fusion-enabled semi-supervised optimal temperature-guided PCL framework for machinery fault diagnosis

Published:2024-01 Issue: Volume:101 Page:102005
ISSN:1566-2535
Container-title:Information Fusion
language:en
Short-container-title:Information Fusion

Author:

Jiang Xingxing^ORCID,Li Xuegang,Wang Qian,Song Qiuyu,Liu Jie,Zhu Zhongkui

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Signal Processing,Software

Reference49 articles.

1. Central frequency mode decomposition and its applications to the fault diagnosis of rotating machines;Jiang;Mech. Mach. Theory,2022

2. Smart multichannel mode extraction for enhanced bearing fault diagnosis;Song;Mech. Syst. Signal Process.,2023

3. An adaptive and efficient variational mode decomposition and its application for bearing fault diagnosis;Jiang;Struct. Health Monit.,2021

4. A novel unsupervised directed hierarchical graph network with clustering representation for intelligent fault diagnosis of machines;Zhao;Mech. Syst. Signal Process.,2023

5. A hybrid domain adaptation diagnostic network guided by curriculum pseudo labels for electro-mechanical actuator;Wang;Reliab. Eng. Syst. Saf.,2022

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