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机构地区:[1]湖南工业大学,株洲412007
出 处:《中国机械工程》2014年第2期174-179,共6页China Mechanical Engineering
基 金:国家自然科学基金资助项目(51375161);湖南省自然科学基金资助项目(11JJ3055);湖南省高等学校科学研究重点项目(11A028)
摘 要:利用金相显微镜对螺旋锥齿轮磨削表层金相组织特征进行检测分析,结果表明,齿轮磨削表面的金相组织为针状马氏体+碳化物+残余奥氏体,心部的组织为板条状低碳马氏体+铁素体+贝氏体。采用正交试验法,分析了不同工艺参数对螺旋锥齿轮表层金相组织的影响规律,根据极差分析得出了磨削最优工艺参数。结果表明,当螺旋锥齿轮小轮凹面磨削工艺参数为磨削深度ap=20μm、砂轮速度vs=35.2m/s、齿轮进给速度vw=0.073m/s时,残余奥氏体量Ar=15.6%,针状马氏体晶粒级别为2级,平均疲劳寿命可达6.0×104次,此时螺旋锥齿轮组织性能最优,可提高齿轮抗疲劳性能和耐磨性。建立了螺旋锥齿轮残余奥氏体量的回归数学模型,计算值和试验测量值相对误差最大绝对值为14.3%,说明该回归数学模型较为有效,其计算结果与残余奥氏体量的试验极差分析结果基本一致。Firstly, this paper used metallographic microscope to observe the surface microstructure characteristics of spiral bevel gears. The results show that metallographic organization of gear grinding surface is acicular martensite+ carbide+residual austenite, carburizing layer metallurgical group is high carbon martensite + carbide + residual austenite, the heart of the department of organization is plate strip low carbon martensite+ferrite+ bainite. Then the influences of different processing param- eters on the spiral bevel gear surface metallurgical structure were analyzed through the orthogonal test method. Lastly,the optimal processing parameters were got through the range analysis. The results show that when the spiral bevel gear small wheel concave grinding process parameters for the depth of grinding ap = 20μm, wheel speed vs = 35.2m/s, workpiece speed Vw = 0. 073m/s, namely austenitic re- sidual volume is 15.6% ,the level of aeicular martensite is level 2,the organization optimal is optimal, so as to improve the influence law of gear fatigue performance and improve the wear resistance. A re- turn content mathematical model of of the retained austenite in spiral bevel gear was established,the calculated value and maximum absolute value relative error of experimental measurements is 14.3%, showing that the regression mathematical model is relatively effective, and content of the retained aus- tenite and experimental range analyses results are basically identical.
关 键 词:螺旋锥齿轮 金相组织 残余奥氏体量 回归数学模型
分 类 号:TH132.41[机械工程—机械制造及自动化]
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