Research on Tool Wear Prediction of Laser-assisted Cutting of Cemented Carbide
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School of Mechanical and Power Engineering,Henan Polytechnic University,Jiaozuo 454003

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TG506.5

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    Abstract:

    As a typical difficult-to-machine material, cemented carbide YG10 was prone to cause severe tool wear when common cutting method was used.In response to this problem,laser-assisted cutting method was proposed for machining.By comparing the tool wear conditions under the two machining methods of ordinary cutting and laser-assisted cutting,it was demonstrated that laser-assisted cutting could effectively reduce cutting force and tool wear.The support vector regression model (SVR) and cross-validation-support vector regression model(CV-SVR)were established,and the amount of flank wear under specific cutting conditions were predicted.The result shows that the prediction results of the two models have a small error with the actual values,in particular,the CV-SVR model has higher fitting accuracy,compared with the SVR model,the average relative error is reduces by about 10%.The CV-optimized SVR model can effectively simulate the nonlinear relationship in tool wear,and it can provide a basis for the judgment of tool wear in actual machining.

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History
  • Received:April 25,2023
  • Revised:June 12,2025
  • Adopted:June 30,2023
  • Online: June 27,2025
  • Published: June 30,2025
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