R410a 冷却液对车削 AISI 1045 钢时刀具磨损、尺寸偏差和表面粗糙度的影响

Gholamreza Khalaj, Mohammad-Javad Haghparast, Mohammad-Sadegh Salari, Alireza Motahari
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引用次数: 0

摘要

在加工过程中,刀具与工件之间的摩擦总是会增加刀具的磨损率。通过使用流体冷却刀具来消除这一问题至关重要。在这项研究中,使用了两种冷却条件:在使用高速钢(HSS)刀具车削 AISI 1045 钢(CK45)时,研究了水溶性切削油(WSCO)液和 R410a 冷却液对刀具磨损率、尺寸偏差和表面粗糙度的影响。所选参数为切削速度 15、25、40 和 55 m/min,切削深度 0.5、1 和 1.5 mm,进给率 0.05、0.12 和 0.2 mm/rev。结果表明,与 WSCO 冷却液相比,R410a 冷却液的冷却能力强,切削区域的温度控制更好,因此降低了刀具磨损率。根据不同条件下刀具磨损、尺寸偏差和表面粗糙度的最小值,使用 R410a 冷却液可将切削速度提高 60%,从 25 米/分钟提高到 40 米/分钟。此外,在切削速度为 40 米/分钟、切削深度为 1 毫米、进给速度为 0.05 毫米/转的最佳条件下,刀具磨损、尺寸偏差和表面粗糙度分别降低了 20 倍、6 倍和 10 倍。在最佳条件下,以 300 mm 直径差为基准的尺寸偏差降低到 14 µm,车削 60 分钟后的刀具磨损率和表面粗糙度也分别降低到 20 µm 和 3.1 µm。每个输入变量对刀具磨损、尺寸偏差和表面粗糙度的影响都通过统计分析进行了计算,并通过方差分析进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effect of R410a coolant on tool wear, dimensional deviation and surface roughness in turning of AISI 1045 steel
Friction between the tool and the workpiece during machining operations always increases the tool wear rate. Removing this problem by using fluids and cooling the tools is essential. In this research, the effects of two cooling conditions: Water Soluble Cutting Oil (WSCO) fluid and R410a coolant, on the tool wear rate, dimensional deviation and surface roughness of AISI 1045 steel (CK45) in turning with a high-speed steel (HSS) tool were investigated. The selected parameters were cutting speeds of 15, 25, 40 and 55 m/min, cutting depths of 0.5, 1 and 1.5 mm and feed rates of 0.05, 0.12 and 0.2 mm/rev. The results show that cooling by R410a coolant reduces the tool wear rate due to its high cooling power and better temperature control at the cutting zone compared to WSCO fluid. Based on the minimums of tool wear, dimensional deviation and surface roughness in different conditions, using R410a coolant can increase the cutting speed by 60% from 25 to 40 m/min. Also, in the optimal condition at a cutting speed of 40 m/min, cutting depth of 1 mm and feed rate of 0.05 mm/rev., tool wear, dimensional deviation and surface roughness are reduced by up to 20, 6 and 10 times respectively. In the optimal condition, the dimensional deviation based on the diameter difference along 300 mm is reduced to 14 µm and also the tool wear rate and surface roughness after 60 min. of turning are reduced to 20 and 3.1 µm respectively. The effect of each input variable on tool wear, dimensional deviation and surface roughness was calculated by statistical analysis and was validated by ANOVA.
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