一种薄壁扇形齿轮磨齿夹具设计

扇形齿轮加工一直是齿轮加工中的难点,尤其是有较高精度要求的扇形薄壁齿轮加工。通过对一种形状复杂的薄壁扇形齿轮结构和工艺分析,选择了薄壁扇形齿轮磨削定位方式和装夹方式,设计了易装夹的磨齿夹具,经实际使用表明,所设计的磨齿夹具能满足薄壁扇形齿轮加工精度要求。     

实现半闭环控制磨削加工的数控改造

数控磨削加工的难点在于,由于砂轮在磨削过程中是不断磨损的,因此使得被磨工件的加工尺寸不能恒定。在普通磨床上采用特殊的数控改造方式,同时采用特殊结构的数控加工程序编制,在磨削过程中可以实现砂轮的修整,达到了半闭环控制的磨削加工效果。在保证被磨工件的尺寸精度的基础上,提高了被磨工件的几何加工精度和生产效率。     

超精密无心磨削的尺寸精度控制

无心磨削与普通外圆磨削类似,亦有纵向磨削（在无心磨削中称之为贯穿磨削）和切入磨创两种磨削形式。其磨削特点是：①磨削时,工件无需中心孔和夹紧机构;②工件上、下料可与磨削同时进行,磨削效率高。因此,无心磨削特别适用于滚动轴承行业中的批量生产。在轴承加工中,尺寸精度是其最重要的精度项目之一,影响尺寸精度的主要因素则有如下三种类型：①微量位置调整与相对于给定值的尺寸设定;②连续加工中的短时间尺寸精度;③连续加工中的长时间尺寸精度。一、微量位置调整与相对于给定值的尺寸设定无心磨床的进给拖板,传统上大都采用…     

磨削加工精度分析及提高方法

磨削的加工精度,指零件磨削加工后的尺寸精度、形状精度和位置精度三方面与图样技术要求所符合的程度。在磨削加工时,磨床、夹具、砂轮和工件构成了一个完整的工艺系统。     

内圆磨床工作热对零件磨削精度影响的研究

对小深孔内圆磨床磨削热对零件尺寸精度的影响进行了探讨。通过因素分析和试验，发现了零件在内圆磨削加工时尺寸精度的变形规律；并研究了磨削热源引起的机床变形对磨削零件尺寸精度的影响；最终提出了磨削加工时的注意事项和补偿措施。     

薄壁圆管内孔珩磨加工专用夹具设计

针对薄壁圆管工件内孔珩磨加工时易出现较大变形而导致加工精度难以保证的问题,通过对掘进机上某薄壁圆管零件的珩磨工艺分析,设计了一种薄壁圆管内壁珩磨专用夹具,改善了薄壁圆管工件的磨削工艺性,提高了加工精度和生产效率。     

细长轴开式砂带磨削试验研究与精度分析

根据砂带磨削的原理、特点、设计一台砂带磨削装置,并将其应用于细长轴的加工,实验中以尺寸精度和圆度误差为研究对象,重点研究砂带磨削后尺寸精度和圆度误差的变化,分析影响砂带磨削加工精度的因素,指出提高砂带磨削精度的措施。实验表明在车床上采用砂带磨削装置进行细长轴磨削,能有效地提高加工精度。     

磨加工主动测量控制仪尺寸预报功能研究

磨加工主动测量控制仪应用于磨削中,提高了磨削精度、磨加工效率与磨削的自动化水平。在深入研究主动测量与误差补偿控制的基础上,研究拓展主动测量控制仪的磨加工尺寸预报功能,预报磨加工过程中的超差,为机床系统修正加工状态提供指引。通过对磨加工过程进行分析,对尺寸预报理论的适用性进行研究,构建了磨加工尺寸灰色补偿式滑动平均组合预报模型。通过实验验证分析,模型平均相对误差为0.0067,均方根误差为0.3173,关联度为0.7682,尺寸预报应用于磨加工主动测量控制仪中,提高了主动量仪的精度与智能化程度,提高了磨加工系统地尺寸测量、预报与误差补偿控制的精度。     

防止薄壁零件内孔磨削变形的工艺方案

在磨削加工大直径薄壁零件时,经常会发生零件内孔变形的现象。以建筑机械中常用的典型大直径薄壁零件——衬套(见图1)为例。该零件材料为45钢,壁厚仅为5mm,需要进行调质处理,内孔表面粗糙度要求为Rα0．8μm,且各尺寸之间的形位精度要求均较高。由于零件直径较大,壁厚较薄,在磨削内孔时,如果不采取有效措施,常常会因为夹紧力、磨削力、磨削热、内应力等原因,使零件产生较大的无规律变形,难以保证零件的内孔加工质量。为减小零件变形,保证其加工质量,我们根据该零件的结构特点,制订了合理的加工工艺方案,并设计了专用磨削夹具,有效保证了零件的加工质量。     

超微米磨削技术——外圆·内圆磨削

前言磨削加工是用微小的多刃刀具切除细微切屑的加工。因此在加工中,另件尺寸产生连续性的变化(切入磨削时)。另外,即使在非连续性磨削的情况下,也可将一次行程尺寸的变化值调得很小。就是说,完全可以使尺寸变化控制在1微米以内,这就是磨削加工的优点。磨削加工是机械加工中决定工件精度的最终工序。我们虽然能定性地掌握磨削加工所产生的切削现象,但是由于磨削加工是由微小切削刃来生成细微切屑的,而且切屑形状尺寸是连续变化的,再则,影响磨削现象的因素又很多,这就很难定量分析。因此,要使图1所示磨削系统的加工精度、加工现象进一步与加工输入条件相对应,就必须有丰富的经验不可。     

智能控制型径向切入磨削加工系统

针对径向切入式磨削加工过程 (尤其是薄壁工件 ) ,提出了一套新的磨削工艺程式及与之相适应的递阶式智能控制模式。其上层是一个基于知识并具有学习能力的智能决策系统 ,它根据加工要求 ,按照当前加工条件 ,自动规划加工参数 ;下层的自适应环节能实现对磨削过程的在线监测和实时控制。仿真与试验结果表明 ,该方法能较好地应用于实际磨削过程 ,可在更短的时间内获得更理想的加工效果。这一系统具备了相当的柔性 ,可以适应小批量多品种的加工要求。     

精密内圆磨削过程的灰色系统模型研究与质量控制系统设计

预报补偿与控制技术是提高精密内圆磨削质量的有效途径。在分析轴承内圈内圆磨削质量的基础上，指出精密内圆磨削过程可视为一典型的灰色系统，灰色系统ＧＭ（１，１）模型将有助于进一步认识内圆磨削过程的本质。建模仿真结果表明，ＧＭ（１，１）模型可以较好地描述工件磨削尺寸误差序列的趋势项，基于此，就可以对内圆磨削过程实施预报补偿控制。设计了旨在提高轴承内圈内圆磨削质量和效率的控制系统。     

细长轴磨削变形的变速优化智能预测控制研究

在建立细长轴磨削过程中工件弹性变形数学模型的基础上，打破了传统的恒速控制方法，提出了一种控制细长轴磨削弹性变形的变速优化适应控制策略：根据磨削系统沿工件轴向各点刚度的不同，通过不断改变工件转速和纵向进给速度，控制法向磨削力的变化，进而控制工件的弹性变形；同时，由一个神经网络预测系统和一个模糊控制系统实时控制加工过程中的磨削深度，进一步控制加工中由于砂轮磨损而引起的细长轴形状误差。仿真和实验结果表明：变速优化适应控制策略和模糊神经网络预测控制方法是可行的，可极大地提高磨削生产率，减小细长轴的形状误差。     

机器人柔顺力控装置研究

机器人自动化抛光过程中,工具与工件间的接触力控制尤为重要.基于主动柔顺控制的原理,提出了面向工业机器人的柔顺力控装置及控制方法.进行了系统的结构设计和动力学建模,基于BP神经网络PID算法,设计了该柔顺力控装置的自适应控制策略.最后进行力控跟踪实验,实验结果表明,柔顺力控装置能够保证打磨过程中工件与工具之间的接触力恒定...     

Modeling and simulation of cutting forces generated during vertical micro-grinding

Micro-grinding using micro-tools has become very prevalent due to the miniaturization of products with increased process requirements. Moreover, this process provides an edge over other competitive processes, especially as a final process step. The quality of the part produced by the micro-scale grinding process can be influenced by various factors, particularly by the induced mechanical forces. Therefore, predictive model of cutting force can provide guidance for further development and optimization of the process. Although there has been a lot of a research conducted on conventional grinding, little knowledge has been accumulated on micro-scale grinding due to the fact that it is an emerging field of research. The early grinding models developed are mostly based on parameters such as wheel and workpiece velocity, depth of cut and grit size of the grinding wheel. Those early models narrated that the grits penetrate and cut the material from the workpiece surface with the generated grinding forces proportional to the removed material. However, those models may not be appropriate for micro-scale grinding due to the mode of material removal and the method of contact between surfaces which is different from the macro-scale method. In addition to that, due to the small feed rate used in brittle material machining, ploughing force needs to be considered intensively in addition to the chip formation force. Therefore, a new analytical model has been proposed to evaluate cutting forces of micro-grinding process based on the process configuration, workpiece material properties and micro-grinding tool topography. The size effect of micro-machining has been carefully considered in this proposed model. Therefore, this approach allows the derivation of cutting force comprising of both the chip formation force and ploughing force. Experimental investigation in a micro-grinding configuration has been pursued to validate the proposed predictive model. The estimated cutting force showed a good correlation with the experimental values except for higher depth of cut and lower feed rate. Additionally, paired T test has been performed to quantify the difference between the predicted and experimental results.     

智能化适应控制系统在磨加工中应用

介绍了一种智能化适应控制磨削加工控制系统理论和方法,综合控制补偿加工中各种因素影响产生的误差。大幅度降低加工零件的尺寸分散度,实现最优控制目标。介绍了控制系统的组成、软硬件设计和工作方法。     

锯片磨削加工的多线程控制策略及实现

为克服开环数控锯片磨床工件尺寸难以精确控制、生产率低等缺点,通过增设工件尺寸实时在线测量系统,构建一个由磨削控制线程和G代码程序组成的多线程控制系统,实现了锯片磨削过程的全闭环控制。此系统在数控平面磨削加工中具有广阔的应用前景。文中着重介绍了采用多线程实现锯片磨削加工控制的方法,以及多线程控制的G代码编程。     

超声振动辅助磨削加工智能控制技术研究

根据超声振动辅助磨削加工的特点,结合检测难易程度和实际需要,选择磨削力比作为输入。利用磨削力检测系统获得磨削力比实时数据,对采样结果进行分析处理。采用分级控制,分别控制超声功率和工件进给速度。将磨削力比的变化和变化率作为模糊控制器的输入,工件进给速度作为控制器的输出。根据模糊控制规则,利用Matlab提供的Simulink仿真模块,对超声振动辅助磨削加工模糊控制系统进行了动态仿真,仿真结果符合模糊策略,进给速度能够随着磨削力比的变化实现调整,从而避免产生磨削烧伤和颤振。     

A simulation platform for optimal selection of robotic belt grinding system parameters

Robotic belt grinding is an effective process for removing material from geometrically complex workpieces. However, due to the relatively low stiffness of the system, the grinding quality is prone to inaccuracies caused by system dynamics. In order to control the quality of the grinding process, a profound understanding of the system is required. This paper presents a platform for comprehensive modeling and simulation of the robotic belt grinding system. The system kinematics model is based on the CAD model of the workpiece in composition with robot kinematics. The dynamics model is a comprehensive combination of the dynamics of the robot, the grinder, and the interaction between the grinder and the workpiece. A material removal model of the grinding process, which can adapt to workpieces with complicated shapes, is also developed and presented. The system simulation shows that optimal selection of key control parameters of the grinder and proper selection of robot control strategies can efficiently suppress chatter in the grinding process. Furthermore, having the ability to predict material removal rate, the comprehensive simulation platform is also demonstrated to be a strong tool in selecting the grinding process key parameters, namely, robotic velocity and contact force, for the control of material removal to meet dimensional accuracy requirements on workpieces.     

Reduced models of grinding wheel topography and material removal to simulate dynamical aspects in grinding

Increasing competition and short product life cycles make it necessary to optimize and evaluate the outcome of manufacturing processes. In tool grinding, models for the final workpiece geometry and cutting forces are of particular interest. To establish a valid general grinding model, we investigated the cutting process and the influence of local grinding wheel engagements on the material removal. We consequently developed models of material removal and grinding wheel topography, which capture the main correlations in grinding. In combination, temporal cutting forces and final workpiece geometry are predictable and are in excellent agreement with experimental data. The introduced models are valid for grinding in general, since they are solely based on the geometry and process parameters, and hence are applicable for manufacturing process optimization.