A dual-stage attention model for tool wear prediction in dry milling operation

HIGHLIGHTS

• who: Yongrui Qin and collaborators from the Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia have published the research: A Dual-Stage Attention Model for Tool Wear Prediction in Dry Milling Operation, in the Journal: Entropy 2022, 24, x FOR PEER REVIEW of /2022/
• what: The main contributions of this paper include three parts: Firstly, to obtain comprehensive signal characteristics, features are extracted from the collected sensor signals during milling cutter processing through three-domain analysis. The model proposed by this paper has a good fitting effect, and the curves Overall,match the . . .
  

   

  

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