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CdualTAL: multi-domain tool wear prediction using a dual-channel Transformer and cross-attention network
Regular Papers | Updated：2026-02-11

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

      Enhanced Publication
    • CdualTAL：基于双通道Transformer和交叉注意力网络的多域刀具磨损预测
    • “In the field of manufacturing efficiency, a new study introduces significant research progress. Experts have developed CdualTAL, an advanced algorithm that enhances tool wear prediction. This innovative system leverages a dual-channel Transformer encoder and a custom cross-attention mechanism to effectively integrate strong and weak features, achieving superior prediction stability and accuracy.”
    • ENGINEERING Information Technology & Electronic Engineering   Vol. 27, Issue 2, Pages: 1-13(2026)

    • DOI：10.1631/ENG.ITEE.2025.0111    

      CLC： TP391.41;TP274

    • Received：01 November 2025，

      Revised：2026-01-31，

      Published：2026-02

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  • 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.

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Related Institution

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