7050铝合金二维超声滚压加工表面完整性综合评价
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摘要
采用正交试验法对7050铝合金进行二维超声滚压加工试验,选取表面粗糙度、表层硬度和残余应力作为表面完整性评价指标,运用灰色关联分析法对表面完整性进行综合评价。通过研究工艺参数对表面粗糙度、表层硬度和表面残余应力的影响,采用多元线性回归方法构建表面完整性各评价指标和灰色关联度预测模型,从而获取最优工艺参数和相应评价指标值。研究结果表明:对于不同的评价指标,各工艺参数的贡献率不同;预测模型在95%置信水平上均通过了显著性检验,可对试验结果进行准确预测;基于预测模型的规划求解所获得的表面完整性结果优于灰色关联度的优选结果,规划求解所获得的最优工艺参数为静压力327 N、转速400 r/min、进给量0.11 mm/r,此时残余应力σ值约为-236.98 MPa,表面粗糙度Ra值约为0.56μm,表层硬度约为695 HL。
The orthogonal tests of two dimensional ultrasonic rolling 7050 aluminum alloys were carried out. The surface roughness,surface hardness and residual stress were selected as the evaluation index of surface integrity. Gray correlation analysis method was used to evaluate the surface integrity. To obtain the optimal process parameters and corresponding evaluation index values,the prediction models for the evaluation index and the grey relational degree were constructed using multiple linear regression method along with studying the effects of process parameters on the surface roughness,surface hardness and surface residual stress. The results indicate that the contribution rates of process parameters are different with different evaluation indexes. The prediction models are significant at 95% confidence level,so they may be used to predict the test results accurately. The results of surface integrity obtained from the models are better than the optimal results selected from grey relational degree. The optimal process parameters obtained by the nonlinear programming solver based on the model are as follows. When the static force is as 327 N,the speed is as 400 r/min and the feed-rate is as 0.11 mm/r,the optimal surface integrity may be obtained with the residual stress-236.98 MPa,the surface roughness Ra 0.56 μm and the microhardness 695 HL.
The orthogonal tests of two dimensional ultrasonic rolling 7050 aluminum alloys were carried out. The surface roughness,surface hardness and residual stress were selected as the evaluation index of surface integrity. Gray correlation analysis method was used to evaluate the surface integrity. To obtain the optimal process parameters and corresponding evaluation index values,the prediction models for the evaluation index and the grey relational degree were constructed using multiple linear regression method along with studying the effects of process parameters on the surface roughness,surface hardness and surface residual stress. The results indicate that the contribution rates of process parameters are different with different evaluation indexes. The prediction models are significant at 95% confidence level,so they may be used to predict the test results accurately. The results of surface integrity obtained from the models are better than the optimal results selected from grey relational degree. The optimal process parameters obtained by the nonlinear programming solver based on the model are as follows. When the static force is as 327 N,the speed is as 400 r/min and the feed-rate is as 0.11 mm/r,the optimal surface integrity may be obtained with the residual stress-236.98 MPa,the surface roughness Ra 0.56 μm and the microhardness 695 HL.
引文
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[11]THAKUR A,GANGOPADHYAY S.State-ofthe-art in Surface Integrity in Machining of Nickelbased Super Alloys[J].International Journal of Machine Tools&Manufacture,2016,100:25-54.
[12]AGARWAL S.Optimizing Machining Parameters to Combine High Productivity with High Surface Integrity in Grinding Silicon Carbide Ceramics[J].Ceramics International,2016,42(5):6244-6262.
[13]于鑫,孙杰,李世涛,等.滚压工艺对EA4T车轴表面质量完整性的影响及预测模型建立[J].中国表面工程,2014,27(5):87-95.YU Xin,SUN Jie,LI Shitao,et al.Influences of Burnishing Process on Surface Quality Integrity of EA4T Axles and Establishment of Prediction Model[J].China Surface Engineering,2014,27(5):87-95.
[14]刘春景,唐敦兵,何华,等.基于灰色关联和主成分分析的车削加工多目标优化[J].农业机械学报,2013,44(4):293-298.LIU Chunjing,TANG Dunbing,HE Hua,et al.Multi-objective Optimization of Turning Based on Grey Relational and Principal Component Analysis[J].Transactions of the Chinese Society for Agricultural Machinery,2013,44(4):293-298.
[15]贾振元,顾丰,王福吉,等.基于信噪比与灰关联度的电火花微小孔加工工艺参数的优化[J].机械工程学报,2007,43(7):63-67.JIA Zhenyuan,GU Feng,WANG Fuji,et al.Parmeter Optimization of EDM Micro-and-small Holes Based on Signal-to-noise and Grey Relational Grade[J].Chinese Journal of Mechanical Engineering,2007,43(7):63-67.
[16]东亚斌,段志善.灰色关联度分辨系数的一种新的确定方法[J].西安建筑科技大学学报(自然科学版),2008,40(4):589-592.DONG Yabin,DUAN Zhishan.A New Determination Method for Identification Coefficient of Grey Relational Grade[J].Journal of Xi’an University of Architecture&Technology(Natural Science Edition),2008,40(4):589-592.
[2]CAO J,LI F,MA X,et al.Study of Fracture Behavior for Anisotropic 7050-T7451 High-strength Aluminum Alloy Plate[J].International Journal of Mechanical Sciences,2017,128/129:445-458.
[3]PANDEY V,CHATTOPADHYAY K,SRINIVAS N C S,et al.Low Cycle Fatigue Behavior of AA7075 with Surface Gradient Structure Produced by Ultrasonic Shot Peening[J].Procedia Structural Integrity,2016,2:3288-3295.
[4]WANG G Q,LEI M K,GUO D M.Interactions between Surface Integrity Parameters on AISI 304Austenitic Stainless Steel Components by Ultrasonic Impact Treatment[J].Procedia Cirp,2016,45:323-326.
[5]LI G,QU S G,PAN Y X,et al.Effects of the Different Frequencies and Loads of Ultrasonic Surface Rolling on Surface Mechanical Properties and Fretting Wear Resistance of HIP Ti–6Al–4V Alloy[J].Applied Surface Science,2016,389:324-334.
[6]罗傲梅,郭伟.纵-扭复合振动超声深滚加工表面强化研究[J].表面技术,2015,44(5):106-110.LUO Aomei,GUO Wei.Research on Surface Strengthening by Ultrasonic Deep Rolling with Longitudinal-Torsional Vibration[J].Surface Technology,2015,44(5):106-110.
[7]ZHU L H,GUAN Y J,WANG Y J,et al.Influence of Process Parameters of Ultrasonic Shot Peening on Surface Roughness and Hydrophilicity of Pure Titanium[J].Surface&Coatings Technology,2017,317:38-53.
[8]陈利钦,项彬,任学冲,等.表面超声滚压处理工艺对高速列车车轴钢表面状态的影响[J].中国表面工程,2014,27(5):96-101.CHEN Liqin,XIANG Bin,REN Xuechong,et al.Influence of Surface Ultrasonic Rolling Processing Parameters on Surface Condition of Axle Steel Used in High Speed Trains[J].China Surface Engineering,2014,27(5):96-101.
[9]ZHENG J X,LIU C S,ZHANG Y M.Basic Research on Ultrasonic Extrusion for 45 Steel Shaft[J].Key Engineering Materials,2011,455:288-292.
[10]SHARMA V,PANDEY P M.Optimization of Machining and Vibration Parameters for Residual Stresses Minimization in Ultrasonic Assisted Turning of 4340 Hardened Steel[J].Ultrasonics,2016,70:172-182.
[11]THAKUR A,GANGOPADHYAY S.State-ofthe-art in Surface Integrity in Machining of Nickelbased Super Alloys[J].International Journal of Machine Tools&Manufacture,2016,100:25-54.
[12]AGARWAL S.Optimizing Machining Parameters to Combine High Productivity with High Surface Integrity in Grinding Silicon Carbide Ceramics[J].Ceramics International,2016,42(5):6244-6262.
[13]于鑫,孙杰,李世涛,等.滚压工艺对EA4T车轴表面质量完整性的影响及预测模型建立[J].中国表面工程,2014,27(5):87-95.YU Xin,SUN Jie,LI Shitao,et al.Influences of Burnishing Process on Surface Quality Integrity of EA4T Axles and Establishment of Prediction Model[J].China Surface Engineering,2014,27(5):87-95.
[14]刘春景,唐敦兵,何华,等.基于灰色关联和主成分分析的车削加工多目标优化[J].农业机械学报,2013,44(4):293-298.LIU Chunjing,TANG Dunbing,HE Hua,et al.Multi-objective Optimization of Turning Based on Grey Relational and Principal Component Analysis[J].Transactions of the Chinese Society for Agricultural Machinery,2013,44(4):293-298.
[15]贾振元,顾丰,王福吉,等.基于信噪比与灰关联度的电火花微小孔加工工艺参数的优化[J].机械工程学报,2007,43(7):63-67.JIA Zhenyuan,GU Feng,WANG Fuji,et al.Parmeter Optimization of EDM Micro-and-small Holes Based on Signal-to-noise and Grey Relational Grade[J].Chinese Journal of Mechanical Engineering,2007,43(7):63-67.
[16]东亚斌,段志善.灰色关联度分辨系数的一种新的确定方法[J].西安建筑科技大学学报(自然科学版),2008,40(4):589-592.DONG Yabin,DUAN Zhishan.A New Determination Method for Identification Coefficient of Grey Relational Grade[J].Journal of Xi’an University of Architecture&Technology(Natural Science Edition),2008,40(4):589-592.