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Tool wear prediction method based on particle swarm optimizationlong and short time memory model
更新时间：2025-05-26

    • Tool wear prediction method based on particle swarm optimizationlong and short time memory model

    • “In the field of turning machining, experts have proposed the PSO-LSTM model, which achieves real-time and accurate monitoring of tool wear status, providing a solution for improving machining stability.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 53, Issue 4, Pages: 989-997(2023)
    • 作者机构：

      武汉理工大学 机电工程学院，武汉 430070

    • DOI：10.13229/j.cnki.jdxbgxb.20210778    

      CLC： TP183

    • Received：12 August 2021，

      Published：01 April 2023

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  • WU Fei,NONG Hao-ye,MA Chen-hao.Tool wear prediction method based on particle swarm optimizationlong and short time memory model[J].Journal of Jilin University(Engineering and Technology Edition),2023,53(04):989-997. DOI： 10.13229/j.cnki.jdxbgxb.20210778.

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