切削参数对树脂聚酰胺-66材料的切削性能影响

The influence of cutting parameters on the cutting performance of resin polyamide-66 material

  • 摘要: 为了研究切削参数对树脂聚酰胺-66材料切削性能的影响规律,采用单因素和响应面法进行试验设计与分析,利用切削试验平台测试了树脂聚酰胺-66材料切削过程的切削力、切削温度和粗糙度。单因素研究表明,当增加切削速度时,切削力逐渐降低,切削温度和粗糙度逐渐增加;当增加进给量和背吃刀量,切削力、切削温度和粗糙度都逐渐增加。通过响应面法分别构建切削参数与切削力、切削温度和表面粗糙度之间的二次回归模型,研究了切削速度、进给量和背吃刀量参数及其交互作用对树脂聚酰胺-66材料切削性能的影响。结果表明:二次回归模型显著,其拟合精度分别为98.89%、99.09%和96.00%,预测出切削速度为90.02 m/min、进给量为0.11 mm/r和背吃刀量为2.0 mm时,切削力最小、切削温度最低和粗糙度最小。对最优切削参数进行切削试验,与预测结果对比,得出切削力分别为32.558 N和31.762 N;切削温度分别为92.5 和90.1 ;粗糙度分别为0.732 μm和0.694 μm,试验值与预测值的误差率分别为2.44%、2.59%和5.19%。

     

    Abstract: In order to study the influence of cutting parameters on the cutting performance of resin polyamide-66 materials, the single factor and response surface method were used for experimental design and analysis. and roughness. The single factor study shows that when the cutting speed is increased, the cutting force gradually decreases, and the cutting temperature and roughness gradually increase; when the feed rate and the amount of back engagement are increased, the cutting force, cutting temperature and roughness all gradually increase. The quadratic regression model between cutting parameters and cutting force, cutting temperature and surface roughness was constructed by the response surface method, and the parameters of cutting speed, feed and back-cut amount and their interaction on the resin polyamide-66 were studied. The effect of cutting properties of materials. The results show that the quadratic regression model is significant, and its fitting accuracy is 98.89%, 99.09% and 96.00%, respectively. The predicted cutting speed is 90.02 m/min, the feed rate is 0.11 mm/r and the back-cut amount is 2.0 mm, the cutting force is the smallest, the cutting temperature is the lowest and the roughness is the smallest. Cutting tests were performed on the optimal cutting parameters and compared with the predicted results,cutting forces of 32.558 N and 31.762 N, cutting temperatures of 92.5℃ and 90.1℃, and roughness of 0.732 μm and 0.694 μm, respectively, with error rates of 2.44%, 2.59%, and 5.19% between the experimental and predicted values, respectively.

     

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