Generalized MAML for few-shot cross-domain fault diagnosis of bearing driven by heterogeneous signals-Reference-Cited by-同舟云学术

Generalized MAML for few-shot cross-domain fault diagnosis of bearing driven by heterogeneous signals

Published:2023-11 Issue: Volume:230 Page:120696
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Lin Jian,Shao Haidong^ORCID,Zhou Xiangdong,Cai Baoping,Liu Bin

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference45 articles.

1. Dual-Threshold Attention-Guided Gan and Limited Infrared Thermal Images for Rotating Machinery Fault Diagnosis Under Speed Fluctuation;Shao;IEEE Transactions on Industrial Informatics,2023

2. Theoretical validation of earlier developed experimental rotor faults diagnosis model;Espinoza-Sepulveda;International Journal of Hydromechatronics,2021

3. Self-supervised learning for tool wear monitoring with a disentangled-variational-autoencoder;Hahn;International Journal of Hydromechatronics,2021

4. Fault diagnosis in industrial rotating equipment based on permutation entropy, signal processing and multi-output neuro-fuzzy classifier;Rajabi;Expert systems with applications,2022

5. Diagnosing rotating machines with weakly supervised data using deep transfer learning;Li;IEEE transactions on industrial informatics,2019

Cited by 30 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. A lightweight residual network based on improved knowledge transfer and quantized distillation for cross-domain fault diagnosis of rolling bearings;Expert Systems with Applications;2024-07

2. A new multi-source information domain adaption network based on domain attributes and features transfer for cross-domain fault diagnosis;Mechanical Systems and Signal Processing;2024-04

3. Graph structure few-shot prognostics for machinery remaining useful life prediction under variable operating conditions;Advanced Engineering Informatics;2024-04

4. Model-Assisted Multi-source Fusion Hypergraph Convolutional Neural Networks for intelligent few-shot fault diagnosis to Electro-Hydrostatic Actuator;Information Fusion;2024-04

5. Rolling bearing intelligent fault diagnosis towards variable speed and imbalanced samples using multiscale dynamic supervised contrast learning;Reliability Engineering & System Safety;2024-03