Hybrid Data Augmentation Combining Screening-Based MCGAN and Manual Transformation for Few-Shot Tool Wear State Recognition-Reference-Cited by-同舟云学术

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Hybrid Data Augmentation Combining Screening-Based MCGAN and Manual Transformation for Few-Shot Tool Wear State Recognition

Published:2024-04-15 Issue:8 Volume:24 Page:12186-12196
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Quan Yu¹,Liu Changfu¹^ORCID,Yuan Zhuang²^ORCID,Yan Boling³

Affiliation:

1. School of Mechanical Engineering, Liaoning Petrochemical University, Fushun, China

2. School of Communication and Information Engineering, Xi'an University of Science and Technology, Xi'an, China

3. School of Mechanical Engineering, Shenyang Jianzhu University, Shenyang, China

Funder

Startup Research Fund of Liaoning Petrochemical University

Liaoning Province Doctoral Research Start-up Fund Project

Fushun Revitalization Talents Program

Basic Scientific Research Project of Liaoning Provincial Department of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10500449/10462905.pdf?arnumber=10462905

Reference36 articles.

1. Deep Spatial-Temporal Feature Extraction and Lightweight Feature Fusion for Tool Condition Monitoring

2. An Intelligent Multiscale Spatiotemporal Fusion Network Model for TCM

3. A novel algorithm for tool wear online inspection based on machine vision

4. A hybrid remaining useful life prediction method for cutting tool considering the wear state

5. Tool wear state recognition based on feature selection method with whitening variational mode decomposition

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