Optimization of ultrasonic rolling extrusion processing parameters of 42CrMo steel based on MOWOA algorithm
To improve the surface quality and fatigue resistance performance of 42CrMo steel parts,the orthogonal experiments were de-signed to analyze the significance of ultrasonic rolling extrusion processing parameters and their influence laws on surface performance in-dexes.Based on experimental data,the BP neural network and exponential regression prediction models were established to verify the accu-racy of the model.The prediction model was optimized by using multi-objective whale algorithm(MOWOA)to perform three-objective and two-objective optimization,and the sets of processing parameters and surface performance optimal parameters were obtained,and the trade-off relationship between surface performance indicators was analyzed.The results show that the exponential prediction model has higher accu-racy and the optimal set of processing parameters is:rotation speed of 210-250 r·min-1,feeding speed of 12-16 mm·min-1,amplitude of 25-28 μm,static pressure of 517-630 N.The optimal set of surface performance parameters is:surface roughness of 0.466-0.507 μm,residual compressive stress of 1002-1110 MPa,microhardness of 709-720 HV.The accuracy of the algorithm was verified by experiments.
ultrasonic rolling extrusionBP neural networkexponential modelMOWOAsurface performance
NETL
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万方数据
