结合在线电解修锐高效磨削陶瓷密封件研究

本文通过设计制作金属结合剂金刚石磨具，结合电解修锐技术对Al2O3陶瓷密封进行了研磨式磨削实验在实验过程中通过检测磨具表面的磨粒出露高度及陶瓷材料的去除量，评价该磨削工艺在陶瓷材料密封件加工中的应用效果。结果表明，电解修锐可有效地修锐金属结合剂金刚石磨具，在加工过程中使磨具保持良好的切削能力，因此材料去除量较大，加大工时短，陶瓷密封件的加工成本得到控制。     

修整成形砂轮的CAD／CHM系统

砂轮修整是成形磨削中的关键技术。本文介绍一种具有较好通用性和实用性的成形砂轮修整ＣＡＤ／ＣＡＭ系统。该系统具有方便灵活的输入方式和良好的人机界面，能够解决各种类型的蜗杆和齿轮的砂轮修整廓形自动生成、自动编程、加工仿真、误差补偿及修整自动控制等问题，同时能满足任意形状的成形砂轮修整要求。     

ELID镜面磨削技术——砂轮快速修整技术的研究

介绍了ELID磨削中采用电火花整形装置对金属结合剂超硬磨料砂轮进行整形修整的技术。修整后的砂轮径向跳动量小于1μm,砂轮表面光滑,形状精度高,磨粒等高性好,适于精密镜面磨削用,具有修整时间短、成本低、砂轮损耗小的优点。     

Applications of Artificial Intelligence to Grinding Operations via Neural Networks

In recent years, artificial intelligence played an important role in machine tool automation. Artificial neural networks, as one of the artificial intelligence algorithms, has superiority in representing the relation between the inputs and outputs of the multi‐variable system. Hence, it can be applied to sophisticated operations such as grinding operation. The aim of this research is to use artificial neural networks as the brain of grinding machine controller. The target of this controller was to achieve the desired workpiece surface roughness under grinding wheel surface topography variations. The core of the system consists of two multi‐layers feed forward artificial neural networks based on back error propagation learning algorithm. The first one was used for process design to achieve the desired surface roughness. It extracts suitable process variables such as grinding wheel speed and feed rate. The second one monitors the cutting operation using sensors' readings. It extracts the different controlling decisions; these are accept the process, redesign the process or start dressing operation under automatic control. According to these decisions, a PC master control program generates the appropriate control codes and sends them to the machine controllers to take the required actions.     

Applications of Artificial Intelligence to Grinding Operations via Neural Networks

In recent years, artificial intelligence played an important role in machine tool automation. Artificial neural networks, as one of the artificial intelligence algorithms, has superiority in representing the relation between the inputs and outputs of the multi-variable system. Hence, it can be applied to sophisticated operations such as grinding operation. The aim of this research is to use artificial neural networks as the brain of grinding machine controller. The target of this controller was to achieve the desired workpiece surface roughness under grinding wheel surface topography variations. The core of the system consists of two multi-layers feed forward artificial neural networks based on back error propagation learning algorithm. The first one was used for process design to achieve the desired surface roughness. It extracts suitable process variables such as grinding wheel speed and feed rate. The second one monitors the cutting operation using sensors' readings. It extracts the different controlling decisions; these are accept the process, redesign the process or start dressing operation under automatic control. According to these decisions, a PC master control program generates the appropriate control codes and sends them to the machine controllers to take the required actions.     

Intelligent diagnostic technique of machining state for grinding

Successful grinding of a final product depends upon a large number of parameters that affect the grinding result and are strongly interlinked. It is, therefore, difficult to detect directly the generation of grinding faults such as chatter vibration and burning. In this paper, to achieve the development of an intelligent diagnostic technique for chatter vibration and burning phenomena on grinding process, acoustic emission signals were processed and signal parameters of the acoustic emission were also determined. In addition, a neural network was used as a diagnostic technique of the grinding state. A momentum coefficient, learning rate, and structure of the hidden layer were determined during the iterative learning process and the performance of the diagnostic technique was evaluated.     

电火花修整金刚石微粉砂轮的磨削特性

地于金属结合剂金刚石微粉砂轮来说，电火花修整法是一种高效的修整方法，本文讨论了电火花后青铜结合剂金刚石微粉砂轮磨削工程陶瓷的磨削力、磨削工件表面粗糙度特性，并同常规磨削法修整进行了比较。     

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。     

杯状砂轮修整器对CBN砂轮的修形及磨削

研究杯状砂轮对陶瓷ＣＢＮ砂轮的修形,及修形后磨削高速钢和软钢的加工特性。通过研究得出,磨削高速钢时砂轮磨粒磨损和切屑附着、磨削软钢时砂轮表面发生堆积物熔着是砂轮磨耗的主要原因。     

陶瓷喷涂层精密镜面磨削技术的研究

１陶瓷喷涂层的结构与特性喷涂层在结构上不同于致密的金属材料。在喷涂过程中，被加热至熔化或接近熔化的粉末材料，或者被加热熔化并雾化的丝材颗粒，在高压气流的带动下撞击到基材表面上，产生变形、流散并冷凝成盘状，镶嵌、咬接和填塞到基材表面上。随后喷来的粒子以...     

基于金刚石微粉烧结棒的超硬砂轮修整试验研究

对金刚石微粉烧结棒修整树脂结合剂金刚石砂轮进行了试验研究.以反映砂轮平面度的端面跳动和径向跳动作为修整效率的评价依据,通过对主轴转速、砂轮组织参数、修整棒进给速度3个方面进行对比试验,得出了以下结论:低主轴转速下修整棒对金刚石砂轮的修整效率较高,砂轮参数对修整效率的影响很小以及修整棒进给速度与修整效率呈非线性关系.     

数字控制成形磨削技术的研究

根据成形磨削的生成原理,建立与成形表面共轭的修整滚轮运动轨迹的数学模型,并通过利用数控装置控制砂轮修整器的二轴运动、精密分度运动和砂轮的径向进给运动,实现数控成形磨削。     

工程陶瓷材料磨削加工工艺研究现状与进展

工程陶瓷材料的可加工性与金属相比相差较多,其加工工艺也与金属存在很大的不同。磨削加工工艺是现今最成熟的陶瓷材料加工工艺,本文综述了近年来国内外工程陶瓷的磨削加工工艺,分析了磨床、砂轮、磨削工艺参数等因素对磨削加工的影响,并阐述了在不同工艺条件下合理选择加工参数的方法。     

基于数值建模的砂轮形貌仿真与测量

建立球形磨粒在空间随机运动的数学模型,提出创建三维砂轮数值模型的方法。提取仿真砂轮的表层磨粒以生成虚拟砂轮形貌,依据振动模型确定的磨粒中心坐标,将球形磨粒转化为不规则六面体进行统计分析。以单点金刚石笔为修整工具,建立修整模型并将其引入砂轮形貌生成过程之中。利用激光传感器测量实际砂轮形貌的磨粒分布规律,并将试验统计数据与同特征的仿真结果相比较,分析两结果之间的区别和联系。通过计算磨粒突出高度、磨粒间距等评价参数,讨论砂轮形貌修整前后的差异,测量和仿真的结果表明：在初始砂轮形貌中,磨粒突出高度呈正态分布,修整后则近似均匀分布,大部分磨粒间距分布在0.2～0.6 mm,为进一步探讨砂轮形貌对磨削工件的影响提供了依据。     

异型螺杆数控磨床的研制

进行异型螺杆磨削时，除了要求机床实现螺旋运动之外，还需要适时进行砂轮截形的计算，并按所计算截形进行砂轮的修整。针对这个要求，研制了异型螺杆数控磨床，实现对异型螺杆整个磨削过程的自动化。     

磨床砂轮智能监测及修整系统

介绍一种具有较好通用性和实用性的砂轮智能监测及修整系统，该系统利用BP神经网络建立声发射(AE)信号、振动信号、砂轮电机功率信号与砂轮磨钝之间的非线性关系，能够根据传感器信号，自动在线监测砂轮磨钝，及时启动砂轮自动修整系统，并且通过采用CNC砂轮自动修整器，能够解决多种类型的成型砂轮的修整。     

新型智能砂轮半自动平衡仪

介绍新研制成功的精密磨床砂轮半自动平衡仪。该仪器利用数字相敏检波技术提取砂轮的不平衡振动信号及最小二乘技术识别砂轮不平衡量;设计出友善的人机界面,用于提示、指导识别与平衡过程;仪器的绝大部分功能均由软件完成,成本低,可靠性高。试验表明仪器原理正确,平衡精度高。     

树脂CBN磨轮的修整对磨轮表面形貌和磨削效果的影响

树脂ＣＢＮ磨轮的修锐方法地磨轮的磨削性能和磨削效果有极大影响。文中通过三种修锐方法的效果比较，说明弹性变板法效果最佳。     

基于Multi-agent的曲轴随动磨削参数智能决策系统

为了实现曲轴随动磨削参数的智能选取及优化,采用多Agent技术构建了参数智能决策系统。分别设计了CBR决策Agent、RBR决策Agent、MBR决策Agent、FR决策Agent及相应功能Agent,这四种推理决策Agent的组合能够互相取长补短,避免仅采用某一技术带来的局限。并且建立了曲轴随动磨削参数的范例库、模型库、规则库和方法库以及各库管理系统。针对曲轴随动磨削参数决策特点,制定统一的协调控制策略,并利用黑板解决各Agent间的通信问题,实现了决策Agent之间的有效协同。     

基于智能化刃磨的车刀位姿调整

本文建立了外圆车刀各刀面的方程式，给出了各刀面从安装初始位姿到刃磨位姿的坐标变换过程．给出了车刀位姿调整机构的传动原理，为智能车刀刃磨机的研制提供了必要的技术保证。