摆线轮修形齿廓成形磨削技术的研究

在分析成形磨削中金刚滚轮制造工艺的基础上,根据摆线啮合副的啮合原理和范成法磨削摆线轮的加工原理及生产实践,利用建立的五种修形方式的数学模型,建立磨削数学模型,应用于数控磨床或光学曲线磨床磨削金刚滚轮基体制造过程中,即可实现修形摆线齿轮的成形磨削.并对范成磨削与成形磨削修形摆线轮特点进行分析,指出在大批量生产中,成形磨削使修形摆线轮的磨削精度高,工艺简化,生产效率高,并且可方便地将两种修形方式应用在摆线轮的修形中,有利于提高摆线啮合副啮合质量,具有范成磨削无法比拟的优点.为修形摆线轮的制造提供了理论基础.     

螺旋锥齿轮最优修形量及齿轮参数选择

本文以降低螺旋锥齿轮传动的噪声为目的;以影响噪声的主要因素冲击动载最小为目标;提出了确定螺旋锥齿轮最佳修缘量和齿轮参数的方法,建立了优化设计的数学模型,进行了实例计算.     

砂带外圆纵磨工艺参数及磨削效果

由于接触轮和砂带都具有一定的弹性,使得砂带磨削与砂轮磨削有许多不同,其中工艺参数对磨削效果产生较大的影响。为了掌握砂带磨削的这一规律,现将砂带外圆纵磨试验分析取得的成果介绍于后。一、试验条件和试验方法 1.试验条件将M120W万能外圆磨床改装成为砂带磨削试验台。     

PLC在一维力解耦砂带磨削机床中的应用

介绍一维力解耦砂带磨削机床的工作原理.阐述了PLC控制一维力解耦砂带磨削机床的原理及其硬件配置和软件设计.     

砂带磨削钛合金磨削加工性能研究

针对钛合金零件干式打磨过程中磨具堵塞引起烧伤的问题,开展锆刚玉砂带和碳化硅砂带干式磨削TC4合金加工试验。通过分析磨削温度、材料去除量、表面完整性及磨粒磨损特征,对砂带磨削钛合金加工工艺进行研究。结果表明：相同磨削用量条件下,锆刚玉砂带相比于碳化硅砂带,磨削温度最高降低23.6%,耐用度提高2倍。磨削表面粗糙度随砂带线速度的增大逐渐降低,且两种砂带磨削表面粗糙度差值呈逐渐增加趋势。当砂带线速度v_s=20 m/s时,锆刚玉砂带比碳化硅砂带磨削表面粗糙度降低了29.7%;当磨削深度增大时,碳化硅砂带磨削表面粗糙度值快速增加,锆刚玉砂带磨削表面粗糙度增量缓慢,当磨削深度增大到0.1 mm时,表面粗糙度差值达到22%。     

摆线针轮修形齿廓数学模型的建立与仿真

在分析现有摆线轮修形理论的基础上,根据摆线啮合副的啮合原理和范成法磨削摆线轮的加工原理和生产实践,建立了包括5种修形方式的统一教学模型,并以BZZ系列全液压转向器的摆线啮合副实际参数为基础,利用MAT-LAB软件进行仿真验证.为摆线针轮啮合副齿廓设计和制造提供了必要的理论基础.     

叶片砂带磨削参数的试验和选择

汽轮机叶片广泛应用1Cr13不锈钢制造。这种材料含铬量高,属马氏体构造。其强度虽接近普通钢,但组织细密,粘韧性大,导热性较差,且有加工硬化现象。用普通砂轮磨削时,切屑易粘附在磨粒上,或者堵塞磨削空隙,降低磨粒的切削作用,增加接触表面的摩擦,使砂轮迅速磨损和钝化。易导致工件表面烧伤。通过试验表明,采用砂带磨削的效果较好。     

基于多传感器融合的砂带磨削参数虚拟测试系统研究

在分析目前砂带磨削参数测试过程中所用方法的基础上 ,指出了多传感器融合的优点及必要性 ,并与单传感器的测试进行了比较。通过分析模糊神经网络的特点及实用价值 ,建立了基于模糊神经网络的方法 ,并应用多传感器融合技术构造了砂带磨削参数虚拟测试系统。     

砂带磨削钛合金表面粗糙度工艺参数的敏感性研究

为了获得给定范围内的砂带磨削钛合金表面粗糙度工艺参数的最优区间,以钛合金TC4为研究对象,进行砂带磨削表面粗糙度试验。构建砂带磨削钛合金表面粗糙度的经验公式,分析表面粗糙度对工艺参数的灵敏度,获得工艺参数的稳定域与非稳定域。结合正交试验中的极差分析,得到工艺参数对表面粗糙度的影响曲线,进行了工艺参数的区间优选。研究结果表明：表面粗糙度对磨料粒度的变化最为敏感,对砂带线速度的变化最不敏感;磨料粒度的优选范围为120#～150#,砂带线速度的优选范围为15～20 m/s,磨削压力的优选范围为10～15 N。本研究对砂带磨削钛合金表面粗糙度控制提供了理论方法与试验依据。     

新型点磨削砂轮磨削参数对磨削温度影响研究

提出了一种带有粗磨区倾角θ的陶瓷结合剂CBN点磨削砂轮,这种新型砂轮具有磨除率高、加工精度好等优点。研究了磨削热产生与分配理论和红外测温原理。分别用不同θ角的砂轮在一系列磨削参数条件下磨削QT700材料的阶梯轴,用Thermovision A40M热像仪测量砂轮磨削工件时接触区的平均温度,得出了偏转角α、磨削深度ap、工件轴向进给速度vf和砂轮速度vs在磨削过程中对磨削温度的影响规律,并且比较了在同一组磨削参数下,三种不同θ角砂轮对磨削温度的影响情况。     

基于图像信息的砂带磨削材料去除率预测模型

砂带磨削广泛应用于工业领域,由于其与工件的柔性接触及砂带磨粒分布的非均匀性,导致砂带磨削中材料去除率难以从理论上精准预估,直接影响砂带磨削效率及其质量控制。基于此提出一种基于火花图像信息的砂带磨削材料去除率识别方法,给出了火花图像的分割处理算法,建立了火花图像的颜色、亮度、面积及轮廓特征的量化特征模型,基于皮尔逊系数分析了火花图像特征与砂带磨削材料去除率之间的相关性,分别建立了基于火花图像单特征的线性回归预测模型和基于支持向量回归(SVR)算法的多特征回归预测模型,采用最大误差、均方差及决定系数作为模型的评价参数,结果表明基于径向基核函数的多特征SVR模型的具有较高的预测精度,决定系数可达0.976。所提出的方法为砂带磨削材料去除率的有效控制提供了一种新途径。     

多工位砂带磨削机床的研究

在机器人砂带磨削系统中,为了磨削复杂曲面的零件,砂带磨削机床需要多种直径的磨削轮和多种磨削方式,为此,研制了多工位砂带磨削机床.讨论了该多工位砂带磨削机床的工作原理,阐述了实现砂带磨削基本磨削方式的结构原理、在线换轮机构及磨削力补偿机构,并进行了实验研究.     

Vibro-impact dynamics of material removal in a robotic grinding process

This paper studies the vibratory dynamics governing material removal performed by a compliant robot. The objective is to understand whether metal removal at a target rate or to a target depth of cut is possible given the unavoidable significant and sustained vibrations inherent to the process. Robotic grinding by the SCOMPI robot developed at Hydro-Québec’s research institute for field maintenance work on hydroelectric equipment is studied. A test rig is developed to investigate the instantaneous process of material removal. The setup employs the methodology of angular analysis to detect and locate the discrete cutting events with respect to the instantaneous angular position of the spindle. Test results confirm that the grinding wheel exhibits cyclic impacting oscillations while removing material. This vibro-impact behavior is explained by the nonsmooth nature of the system arising from the substantial difference between process stiffness and stiffness of the robot. Grinding force and power are formulated based on the impacting dynamics of material removal (impact cutting). Parameters of the impact-cutting model are determined experimentally. The impact-cutting model is found well-suited to predicting the grinding power required to remove metal at a target rate. The conclusion is reached that metal removal to a target depth and with acceptable surface waviness is possible despite high-amplitude vibro-impacts between the grinding wheel and workpiece.     

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.     

In-process endpoint detection of weld seam removal in robotic abrasive belt grinding process

This paper proposes a novel approach for in-process endpoint detection of weld seam removal during robotic abrasive belt grinding process using discrete wavelet transform (DWT) and support vector machine (SVM). A virtual sensing system is developed consisting of a force sensor, accelerometer sensor and machine learning algorithm. This work also presents the trend of the sensor signature at each stage of weld seam evolution during its removal process. The wavelet decomposition coefficient is used to represent all possible types of transients in vibration and force signals generated during grinding over weld seam. “Daubechies-4” wavelet function was used to extract features from the sensors. An experimental investigation using three different weld profile conditions resulting from the weld seam removal process using abrasive belt grinding was identified. The SVM-based classifier was employed to predict the weld state. The results demonstrate that the developed diagnostic methodology can reliably predict endpoint at which weld seam is removed in real time during compliant abrasive belt grinding.     

拖料式定量皮带秤的皮带速度选择讨论

拖料式定量皮带秤可通过出料口闸门开度调整物料流的高度h和通过变频器转速调整皮带速度V以实现给料量自动控制,但在生产现场往往出现超出额定流量的备用余量过小甚至达不到额定流量的问题,笔者建议制造厂商在选择定量皮带秤的皮带速度时应考虑用户加大量程的可能性。     

砂带低速抛磨的可行性研究

针对生产实际中采用的砂带磨削速度普遍与工艺手册的推荐值存在较大差距的问题,以砂带粒度、磨削速度、每转进给量、工件材料四因素进行正交试验设计,确定了各个参数对零件抛光质量的影响。列举了注胚模具型芯零件砂带低速抛光的工程案例,对该零件进行了工艺分析,编制了机械加工工艺,重点介绍了成型面的砂带低速抛光工序。试验结果的极差分析表明,砂带粒度对表面粗糙度的影响最大,远大于其他三因素,然后依次为工件材料、磨削速度,影响最小的是每转进给量;工程实践结果证明,只要选用的砂带粒度合适,即使选用较低的磨削速度,也可以取得良好的抛光效果。