·1214· 工程科学学报，第39卷，第8期 1200 一N预测值 1200 (a) (b) N预测值 ,1000 N实验值 1000 ◆N实验值 800 800 600 400 400◆ 200 0 123456789101112 0123456789101112 实验号 实验号 图10切削能预测模型和实验验证对比曲线.(a)剪切能对比曲线：(b)摩擦能对比曲线 Fig.10 Experimental verification of cutting energy forecasting model:(a)shear energy comparison;(b)friction energy comparison 先增加后减小的趋势，说明使用较大或者较小的进给 (9):1941 量有利于在保证切削系统刚度前提下减小系统误差. [4]Balogun V A,Gu H,Mativenga P T.Improving the integrity of 综上所述，剪切能和摩擦能预测模型拟合程度相对较 specific cutting energy coefficients for energy demand modelling. Proc Inst Mech Eng,Part B:J Eng Manufacture,2015,229 好，此两预测模型具有相对高的可靠性. (12):2109 4结论 [5]Balogun V A,Mativenga P T.Impact of un-deformed chip thick- ness on specific energy in mechanical machining processes.J 本文主要关注304不锈钢专用新型硬质合金微坑 Cleaner Prod,2014,69:260 车刀同原车刀切削能的对比研究及新型微坑车刀切削 [6]Wang B,Liu Z Q,Song Q H,et al.Proper selection of cutting 能的预测，结论如下 parameters and cutting tool angle to lower the specific cutting ener- (1)在以实际生产推荐切削参数，干式切削情况 gy during high speed machining of 7050-T7451 aluminum alloy.J Cleaner Prod,2016,129:292 下，新型微坑车刀相比较原车刀，单位体积输入能量降 [7]Akyildiz H K,Livatyali H.Effect of cutting energy on fatigue be- 低8.96%，剪切能降低10.5%，摩擦能降低5.32%；刀 havior of threaded specimens.Int J Ade Manuf Technol,2014,70 具前刀面的切削温度与剪切能和摩擦能呈正相关关 (1):547 系，新型微坑车刀较原车刀切削温度降低. [8] Bhushan R K.Optimization of cutting parameters for minimizing (2)对新型微坑车刀进行回归正交试验，建立了 power consumption and maximizing tool life during machining of Al 剪切能和摩擦能的预测模型，且从研究因素显著性还 alloy SiC particle.J Cleaner Prod,2013,39:242 可看出，进给量对该预测模型可靠性有较显著影响，其 [9]Zhang Y Z.Metal Cutting Theory.Beijing:Aviation Industry Press,1988 次是切削深度，切削速度影响较小 (张幼桢.金属切削理论.北京：航空工业出版社，1988) (3)通过设计合理的验证性切削实验方案，验证 [10]Li B,Deng J X,Duan Z X,et al.Simulation and experiment of 所建立切削能预测模型的可靠性，结果表明，较大或者 cutting temperature field considering property of materials and 较小的进给量有利于降低实验误差，剪切能预测模型 friction.JMech Eng.2010,46(21):106 和摩擦能预测模型具有相对高的可靠性，可为复杂切 (李彬，邓建新，段振兴，等。考虑材料与摩擦特性的切削温 削条件下的切削能预测及前刀面切削温度研究提供 度场仿真与试验.机械工程学报，2010,46(21)：106) 参照 [11]Chen R Y.Metal Cutting Principle.2nd Ed.Beijing:Machinery Industry Press,2012 参考文献 (陈日曜.金属切削原理.2版.北京：机械工业出版社， 2012) [1]Xie J,Luo M J,Wu KK,et al.Micro-grinding of micro-grooved [12]Camposeco-Negrete C.Najera J D C,Miranda-Valenzuela J C. rake surface of CBN cutter influencing dry cutting temperature.J Optimization of cutting parameters to minimize energy consump- Mech Eng,2014,50(11):192 tion during turning of AlSI 1018 steel at constant material removal (谢晋，罗敏健，吴可可，等.CBN车刀前刀面微沟槽结构磨 rate using robust design.Int J Adr Manuf Technol,2016,83 削及其对干切削温度的影响.机械工程学报，2014,50(11)： (5):1341 192) [13]Gu L Y,Kang G Z,Chen H,et al.On adiabatic shear fracture [2]Ma J,Ge X.Chang S 1,et al.Assessment of cutting energy con- in high-speed machining of martensitic precipitation-hardening sumption and energy efficiency in machining of 4140 steel.Int stainless steel.J Mater Proc Technol,2016,234:208 Adv Manuf Technol,2014,74(9):1701 [14] Zhong QQ,Tang R Z,Lii J X,et al.Evaluation on models of [3]Wu X.Li L,Zhao M,et al.Experimental investigation of specif- calculating energy consumption in metal cutting processes:a case ic cutting energy and surface quality based on negative effective of external tumning process.Int Ade Manuf Technol,2016,82 rake angle in micro turning.Int J Adv Manuf Technol,2016,82 (9):2087工程科学学报,第 39 卷,第 8 期 图 10 切削能预测模型和实验验证对比曲线. (a) 剪切能对比曲线; (b) 摩擦能对比曲线 Fig. 10 Experimental verification of cutting energy forecasting model: (a) shear energy comparison; (b) friction energy comparison 先增加后减小的趋势,说明使用较大或者较小的进给 量有利于在保证切削系统刚度前提下减小系统误差. 综上所述,剪切能和摩擦能预测模型拟合程度相对较 好,此两预测模型具有相对高的可靠性. 4 结论 本文主要关注 304 不锈钢专用新型硬质合金微坑 车刀同原车刀切削能的对比研究及新型微坑车刀切削 能的预测,结论如下. (1)在以实际生产推荐切削参数,干式切削情况 下,新型微坑车刀相比较原车刀,单位体积输入能量降 低 8郾 96% ,剪切能降低 10郾 5% ,摩擦能降低 5郾 32% ;刀 具前刀面的切削温度与剪切能和摩擦能呈正相关关 系,新型微坑车刀较原车刀切削温度降低. (2)对新型微坑车刀进行回归正交试验,建立了 剪切能和摩擦能的预测模型,且从研究因素显著性还 可看出,进给量对该预测模型可靠性有较显著影响,其 次是切削深度,切削速度影响较小. (3)通过设计合理的验证性切削实验方案,验证 所建立切削能预测模型的可靠性,结果表明,较大或者 较小的进给量有利于降低实验误差,剪切能预测模型 和摩擦能预测模型具有相对高的可靠性,可为复杂切 削条件下的切削能预测及前刀面切削温度研究提供 参照. 参 考 文 献 [1] Xie J, Luo M J, Wu K K, et al. Micro鄄grinding of micro鄄grooved rake surface of CBN cutter influencing dry cutting temperature. J Mech Eng, 2014, 50(11): 192 (谢晋, 罗敏健, 吴可可, 等. CBN 车刀前刀面微沟槽结构磨 削及其对干切削温度的影响. 机械工程学报, 2014, 50(11): 192) [2] Ma J, Ge X, Chang S I, et al. Assessment of cutting energy con鄄 sumption and energy efficiency in machining of 4140 steel. Int J Adv Manuf Technol, 2014, 74(9): 1701 [3] Wu X, Li L, Zhao M , et al. Experimental investigation of specif鄄 ic cutting energy and surface quality based on negative effective rake angle in micro turning. Int J Adv Manuf Technol, 2016, 82 (9): 1941 [4] Balogun V A, Gu H, Mativenga P T. Improving the integrity of specific cutting energy coefficients for energy demand modelling. Proc Inst Mech Eng, Part B: J Eng Manufacture, 2015, 229 (12): 2109 [5] Balogun V A, Mativenga P T. Impact of un鄄deformed chip thick鄄 ness on specific energy in mechanical machining processes. J Cleaner Prod, 2014, 69: 260 [6] Wang B, Liu Z Q, Song Q H, et al. Proper selection of cutting parameters and cutting tool angle to lower the specific cutting ener鄄 gy during high speed machining of 7050鄄鄄T7451 aluminum alloy. J Cleaner Prod, 2016, 129: 292 [7] Akyildiz H K, Livatyali H. Effect of cutting energy on fatigue be鄄 havior of threaded specimens. Int J Adv Manuf Technol, 2014, 70 (1): 547 [8] Bhushan R K. Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle. J Cleaner Prod, 2013, 39: 242 [ 9 ] Zhang Y Z. Metal Cutting Theory. Beijing: Aviation Industry Press,1988 (张幼桢. 金属切削理论. 北京: 航空工业出版社, 1988) [10] Li B, Deng J X, Duan Z X, et al. Simulation and experiment of cutting temperature field considering property of materials and friction. J Mech Eng, 2010, 46(21): 106 (李彬, 邓建新, 段振兴, 等. 考虑材料与摩擦特性的切削温 度场仿真与试验. 机械工程学报, 2010, 46(21): 106) [11] Chen R Y. Metal Cutting Principle. 2nd Ed. Beijing: Machinery Industry Press, 2012 (陈日曜. 金属切削原理. 2 版. 北京: 机械工业出版社, 2012) [12] Camposeco鄄Negrete C, N佗jera J D C, Miranda鄄Valenzuela J C. Optimization of cutting parameters to minimize energy consump鄄 tion during turning of AISI 1018 steel at constant material removal rate using robust design. Int J Adv Manuf Technol, 2016, 83 (5): 1341 [13] Gu L Y, Kang G Z, Chen H, et al. On adiabatic shear fracture in high鄄speed machining of martensitic precipitation鄄hardening stainless steel. J Mater Proc Technol, 2016, 234: 208 [14] Zhong Q Q, Tang R Z, L俟 J X, et al. Evaluation on models of calculating energy consumption in metal cutting processes: a case of external turning process. Int J Adv Manuf Technol, 2016, 82 (9): 2087 ·1214·