Rotating machinery fault detection and diagnosis based on deep domain adaptation: A survey-Reference-Cited by-同舟云学术

Rotating machinery fault detection and diagnosis based on deep domain adaptation: A survey

Published:2021-11 Issue: Volume: Page:
ISSN:1000-9361
Container-title:Chinese Journal of Aeronautics
language:en
Short-container-title:Chinese Journal of Aeronautics

Author:

ZHANG Siyu,SU Lei^ORCID,GU Jiefei,LI Ke,ZHOU Lang,PECHT Michael^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Mechanical Engineering,Aerospace Engineering

Reference158 articles.

1. Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging;Li;Chin J Aeronaut,2020

2. A new bearing fault diagnosis method based on modified convolutional neural networks;Zhang;Chin J Aeronaut,2020

3. A novel fault diagnosis algorithm for rotating machinery based on a sparsity and neighborhood preserving deep extreme learning machine;Li;Neurocomputing,2019

4. Applications of machine learning to machine fault diagnosis: a review and roadmap;Lei;Mech Syst Signal Process,2020

5. Zhang J, Li WQ, Ogunbona P, et al. Recent advances in transfer learning for cross-dataset visual recognition: a problem-oriented perspective. 2017:arXiv: 1705.04396[cs.CV]. https://arxiv.org/abs/1705.04396

Cited by 57 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

1. Semi-supervised source-free domain adaptation method via diffusive label propagation for rotating machinery fault diagnosis;Reliability Engineering & System Safety;2024-12

2. Dual-loss nonlinear independent component estimation for augmenting explainable vibration samples of rotating machinery faults;Neurocomputing;2024-12

3. A hybrid transfer learning to continual learning strategy for improving cross-building energy prediction in data increment scenario;Journal of Building Engineering;2024-10

4. An Audio-Based Motor-Fault Diagnosis System with SOM-LSTM;Applied Sciences;2024-09-12

5. TSMDA: intelligent fault diagnosis of rolling bearing with two stage multi-source domain adaptation;Measurement Science and Technology;2024-08-08