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目的：研究切削参数对300 M超高强度钢加工表面质量的影响。方法选用硬质合金刀具车削加工300 M超高强度钢,研究切削参数对表面加工硬化、残余应力及表面粗糙度的影响。通过HXD-1000显微硬度检测仪、X-350 A型X射线应力测试系统、TR240表面粗糙度测量仪对实验过程进行检测分析。通过单因素试验研究影响表面粗糙度的主次因素,并通过正交试验,以进给量f、切削速度v、刀尖圆弧半径rε、背吃刀量ap为变量建立表面粗糙度的预测模型。结果背吃刀量ap=0.2 mm,切削速度v为60~120 m/min,进给量f为0.1~0.25 mm/r时,300M钢经切削加工后,维氏硬度在467~550HV范围内变化。切削速度从60 m/min增大至200 m/min时,表面残余应力从压应力-59.13 MPa变为拉应力257.33 MPa,次表层残余应力的最大残余压应力从-147.46 MPa增大到-422.65 MPa,并且层深至50μm左右处,工件材料的加工变质层结束。结论表面硬度随着进给量和切削速度的增大而减小,并且越往里层,硬度越低,直至达到基体的硬度。影响表面粗糙度的最主要因素为进给量,其次是刀尖圆弧半径,再次为切削速度,背吃刀量对表面粗糙度的影响最小。建立的表面粗糙度预测模型通过了试验验证,具有很高的加工精度。

Objective To study the influence of cutting parameters on the processed surface quality of 300M ultrahigh strength steel. Methods Carbide tool was selected for the turning processing of 300M ultrahigh strength steel, then to study the influence of cutting parameters on surface hardening ,residual stress and surface roughness. HXD-1000 micro-hardness measuring instrument, X-ray stress test system and the surface roughness measuring instrument TR240 were used for measuring and analyzing the experi-mental process. Through single factor experiment, the primary and secondary factors affecting surface roughness were studied. Through orthogonal experiment, with feed f, cutting speed v, tip arc radius rε, turning back ap as variables, the forecast model of surface roughness was established. Results When the cutting parameters were turning back ap=0. 2 mm, cutting speed v=60~120 m/min, feed f=0. 1 ~0. 25 mm/r, after machining, the Vickers hardness of 300 M steel changed in the range of 467HV ~550HV. When the cutting speed increased from 60 m/min to 120 m/min, the surface residual compressive stress increased from-59. 13 MPa to 257. 33 MPa, the subsurface residual compressive stress increased from -147. 46 MPa to -422. 65 MPa, and the deepest affected layer of workpiece materials was about 50 microns. Conclusion With increasing feeding and cutting speed, the surface hardness decreased and the farther from the surface layer, the lower the hardness until reaching the hardness of the matrix. The main influencing factor of surface roughness was feeding, followed by the tip arc radius and cutting speed, while the depth of cut had the minimal influence on surface roughness. The surface roughness prediction model established in this paper passed the experimental verification, and had very high machining accuracy.