【作者】 肖鹏；

【导师】 余剑武； 朱浩；

【作者基本信息】 湖南大学 ， 机械制造及其自动化， 2009， 硕士

【摘要】 钛合金材料具有许多优异的物理机械性能,如高的比强度、耐高温、热强性高等,在航空航天、汽车、工具、模具等领域得到日益广泛的应用。然而,也正因为钛合金的材料特性,给传统的磨削加工方式带来了极大的挑战,如化学活性大高,材料热导率低且热强性高,使磨削力大,磨削温度高,易堵塞和粘附砂轮,造成加工表面层形成较大的残余拉应力,表面粗糙度差,砂轮寿命低,极易产生磨削烧伤和表面/亚表面裂纹等。这极大地增加了钛合金材料的加工成本,严重地阻碍了其进一步的推广应用。超高速磨削技术是通过提高砂轮线速度来改善表面加工质量或提高加工效率的一种现代加工技术,具有磨削力小、磨削温度低,工件变形小,砂轮寿命长等特点,被誉为“现代磨削技术的最高峰”。对比分析钛合金传统磨削难点与超高速磨削特点可以发现,超高速磨削具有解决钛合金高效精密加工的潜力。文献检索表明目前国内外对钛合金超高速磨削工艺方面的研究还很少,有些领域甚至是空白。针对于此,本文以应用最普遍的钛合金材料——TC4为研究对象,在湖南大学自主开发的314m/s超高速磨削试验台进行了超高速磨削工艺试验,在此基础上系统研究了磨削工艺参数对磨削力及表面完整性(包括表面粗糙度、材料表面硬化层的微观硬度与白层)的影响,得出以下结论:(1)采用超高速磨削技术进行钛合金TC4的磨削,可以有效地降低磨削力,减少砂轮的粘附,并获得较好的表面粗糙度。(2)在钛合金TC4的高速超高速磨削工艺中,工艺参数对单位面积磨削力的影响较大:单位面积法向磨削力与切向磨削力Ft均随磨削深度ap和工件速度vw的增大而增大,随砂轮线速度的升高而减小。(3)在钛合金的超高速磨削表面存在白层和热影响层,在超高速磨削条件下,白层的厚度较薄。磨削深度的增大使得磨削力和比磨削能均增大,相变的机会增多,故白层厚度随磨削深度的增大而增大;亚表面微观硬度变化规律与白层、热影响层厚度有很好的相关性。(4)以砂轮线速度、磨削深度和工件速度作为输入特征量,采用BP神经网络对工件表面粗糙度值进行预测。结果表明这种方法能够有效实现钛合金TC4超高速磨削的表面粗糙度预测,预测结果与试验结果趋势基本一致。更多还原

【Abstract】 Titanium alloy is one of typical difficult-to-machine materials, and is widely used in industries due to its excellent properties. But there are many disadvantages such as high grinding force, high grinding temperature in the grinding process of titanium alloy, result in surface burn, residual stress and worse quality. Ultra-high speed grinding can improve the surface quality and productivities by high grinding wheel speed, which has low grinding temperature, low grinding force, low deformation. By comparison of advantages of conventional grinding and ultra-high speed grinding, ultra-high speed grinding is regarded to an efficiency method to machine titanium alloys.From literatures review, it is known that there are a few studies on grinding of titanium alloy. The purpose of this study aim at ultra-high speed grinding technology on titanium alloy grinding on 314m/s grinder designed by Hunan University. By analysis of surface integrity of titanium alloy, some conclusions are drawn as following:(1) It reduced the grinding force and cling to grinding wheel while titanium alloy is machined by ultra-high speed grinding method, therefore, better surface roughness was obtained.(2) The process parameters affect grinding force per area greatly in the process of ultra-high speed grinding of titanium alloy. Normal and tangible grinding force per area becomes bigger with increasing of grinding depth and workpiece speed. But grinding force per area decrease at high grinding wheel speed.(3) The white layer and heat-affected layer exist on the surface/subsurface of titanium alloy, and the thickness of white layer is thin. The bigger grinding depth, the thicker white layer is. The change if micro hardness is consistent with thickness of white layer and heat-affected layer.(4) It predicted the surface roughness of titanium alloy by method of BP neural network which grinding wheel speed, grinding depth and workpiece speed are used as input parameter. The simulation results shows BP neural network method can be used to predict surface roughness, and it is basically consistent with experimental results.更多还原