MTSNN: A Few-Shot Fine-Grained Diagnosis Framework for Cross-Machine Fault Diagnosis With Heterogeneous Fault Categories-Reference-Cited by-同舟云学术

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MTSNN: A Few-Shot Fine-Grained Diagnosis Framework for Cross-Machine Fault Diagnosis With Heterogeneous Fault Categories

Published:2025 Issue: Volume:74 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Li Jipu¹^ORCID,Yue Ke²^ORCID,Wu Zhaoqian¹^ORCID,Jiang Fei¹^ORCID,Zhong Zhi¹^ORCID,Zhang Shaohui¹^ORCID,Li Weihua³^ORCID

Affiliation:

1. School of Mechanical Engineering, Dongguan University of Technology, Dongguan, China

2. Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, Guangdong, China

3. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, Guangdong, China

Funder

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10764799/10930592.pdf?arnumber=10930592

Reference43 articles.

1. Wavelet transform for rotary machine fault diagnosis:10 years revisited

2. Multiple Source-Free Domain Adaptation Network Based on Knowledge Distillation for Machinery Fault Diagnosis

3. Information-Imbalance Learning With Hazard-Sensitive Loss for Machine Fault Diagnosis

4. Machinery cross domain degradation prognostics considering compound domain shifts

5. Model-Assisted Multi-source Fusion Hypergraph Convolutional Neural Networks for intelligent few-shot fault diagnosis to Electro-Hydrostatic Actuator

Cited by 2 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 bearing fault diagnosis method for hydrodynamic transmissions integrating few-shot learning and transfer learning;Scientific Reports;2025-05-30

2. Few-Shot Diffusion Domain Generalization for Diagnosing Joint Reducer Faults in Industrial Robots;IEEE Transactions on Instrumentation and Measurement;2025

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