Research on Modeling and Prediction of Random Cutting Forces in Turning
Aiming at the non-uniformity of turning materials and actual machining conditions such as multi-mode machining systems,a model for predicting random cutting forces is proposed.The constant cutting coefficient in the deterministic model was transformed into a stationary Gaussian process,and the tool vibration and uncut chip thickness were modeled using a stochastic model.The stochastic cutting coefficients are estimated experimentally and effectively simulated using stochastic differential equa-tions at arbitrary time scales.Combining the stochastic model with the multimodal dynamic equation,the numerical prediction of the stochastic cutting force is carried out.To this end,a three-modal machining system was established and tested on workpieces with different metal alloys.The results show that the estimated random cutting coefficient is not sensitive to cutting parameters,and the predicted results are in good agreement with the experimental results in the time and statistical domains.In the case where cutting force cannot be measured online,the model can provide a reference for tool condition monitoring.
Random Cutting ForceStationary Gaussian ProcessCutting CoefficientTurning
万方数据
维普
