Dynamic Vision Enabled Contactless Cross-Domain Machine Fault Diagnosis with Neuromorphic Computing-Reference-Cited by-同舟云学术

Dynamic Vision Enabled Contactless Cross-Domain Machine Fault Diagnosis with Neuromorphic Computing

Published:2024-03 Issue:3 Volume:11 Page:788-790
ISSN:2329-9266
Container-title:IEEE/CAA Journal of Automatica Sinica
language:
Short-container-title:IEEE/CAA J. Autom. Sinica

Author:

Chen Xinrui¹^ORCID,Li Xiang¹^ORCID,Yu Shupeng¹^ORCID,Lei Yaguo¹^ORCID,Li Naipeng¹^ORCID,Yang Bin¹^ORCID

Affiliation:

1. Xi'an Jiaotong University,Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System,Xi'an,China,710049

Funder

National Key R&D Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6570654/10433374/10433405.pdf?arnumber=10433405

Reference18 articles.

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2. RMA-CNN: A Residual Mixed-Domain Attention CNN for Bearings Fault Diagnosis and its Time-Frequency Domain Interpretability

3. Advancing Predictive Maintenance: A Study of Domain Adaptation for Fault Identification in Gearbox Components

4. Wavelet Denoising Applied to Hardware Redundant Systems for Rolling Element Bearing Fault Detection

5. Experimental-Based Fault Diagnosis of Rolling Bearings Using Artificial Neural Network

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