CdualTAL：基于双通道Transformer和交叉注意力网络的多域刀具磨损预测

李娜; 刘振栋; 王枭; 蒋迦旻; 魏彦杰

doi:10.1631/ENG.ITEE.2025.0111

Your Location：

Home >

Browse articles >

CdualTAL：基于双通道Transformer和交叉注意力网络的多域刀具磨损预测

常规文章 | Updated：2026-02-11

- CdualTAL：基于双通道Transformer和交叉注意力网络的多域刀具磨损预测
  Enhanced Publication
- CdualTAL: multi-domain tool wear prediction using a dual-channel Transformer and cross-attention network
- “在制造效率领域，一项新的研究介绍了重大的研究进展。专家们开发了CdualTAL，这是一种增强刀具磨损预测的先进算法。该创新系统利用双通道Transformer编码器和自定义交叉注意力机制，有效地整合了强弱特征，实现了卓越的预测稳定性和准确性。”
- 工程•信息与电子工程（英文） 2026年27卷第2期页码：1-13
- Affiliations：
  
  1.School of Intelligent Manufacturing and Control Engineering, Qilu Institute of Technology, Jinan 250200, China
  2.Shandong Provincial Key Laboratory of Industrial Big Data and Intelligent Manufacturing, Jinan 250200, China
  3.School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai 201209, China
  4.Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Author bio：
  
  ✉Zhendong LIU, liuzd2000@126.com
- Funds：
- DOI：10.1631/ENG.ITEE.2025.0111
  中图分类号： TP391.41;TP274
- 收稿：2025-11-01，
  
  修回：2026-01-31，
  
  纸质出版：2026-02
- Accepted：
Scan QR Code
李娜, 刘振栋, 王枭, 等. CdualTAL：基于双通道Transformer和交叉注意力网络的多域刀具磨损预测[J]. 工程•信息与电子工程（英文）, 2026,27(2):1-13.

Na LI, Zhendong LIU, Xiao WANG, et al. CdualTAL: multi-domain tool wear prediction using a dual-channel Transformer and cross-attention network[J]. ENGINEERING Information Technology & Electronic Engineering, 2026, 27(2): 1-13.
李娜, 刘振栋, 王枭, 等. CdualTAL：基于双通道Transformer和交叉注意力网络的多域刀具磨损预测[J]. 工程•信息与电子工程（英文）, 2026,27(2):1-13. DOI： 10.1631/ENG.ITEE.2025.0111.

Na LI, Zhendong LIU, Xiao WANG, et al. CdualTAL: multi-domain tool wear prediction using a dual-channel Transformer and cross-attention network[J]. ENGINEERING Information Technology & Electronic Engineering, 2026, 27(2): 1-13. DOI： 10.1631/ENG.ITEE.2025.0111.

浏览量

103

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

An attention mechanism-based multi-domain feature fusion approach for active sonar target recognition

Algorithm for 3D point cloud steganalysis based on composite operator feature enhancement

Attention-based efficient robot grasp detection network

Exploring nonlinear spatiotemporal effects for personalized next point-of-interest recommendation

Underwater object detection by fusing features from different representations of sonar data

CdualTAL：基于双通道Transformer和交叉注意力网络的多域刀具磨损预测

CdualTAL: multi-domain tool wear prediction using a dual-channel Transformer and cross-attention network

DOI：10.1631/ENG.ITEE.2025.0111