浅析利用软件分析法合理设计机床主轴支撑跨距

本文主要介绍了在机床设计时,如何利用软件分析技术合理计算主轴支撑跨距,从而提高机床的切削性能。     

高速磁悬浮机床主轴的离散变结构控制

研究了高速磁悬浮机床主轴的变结构控制, 建立了考虑切削过程的主轴 磁轴承系统动力学模型, 并以磁轴承为控制对象, 设计了离散变结构控制器来抑制主轴振动. 仿真结果表明, 变结构控制律对于阶跃、冲击及切削等扰动具有很强的抑制能力, 对系统模型摄动及复杂加工过程具有良好的适应能力.     

基于蚁群算法的直升机舰面系留索预紧力优化

根据直升机在舰面系留时的受力情况,提出一种以直升机6个刚体位移为变量的系留载荷计算方法。针对系留索预紧力优化属于多变量连续空间优化这一特点,采用嵌入确定性搜索的连续域蚁群算法对系留索预紧力进行优化,并在算法中加入MMAS策略,防止算法过早陷入局部最优解。结果表明,该蚁群算法经过二十多步迭代后能够使目标值稳定地收敛,较好地解决了直升机系留索预紧力优化问题。最后,对某型直升机无预紧力和预紧力优化后的系留载荷进行对比分析,无预紧力时多条索具持续松弛未起到系留作用,而预紧力优化后系留索最大张力降低了35.02%,且索具张力分布更均匀。     

静态与冲击载荷作用下偏斜齿轮的有限元分析

利用大型有限元分析软件ANSYS对一个因预紧力不够而偏斜的输出齿轮建立了有限元模型．利用通用ANSYS进行了静态分析,其中在施加力的载荷时．只加在1／4的齿宽上,得到了静态下的应力及变形．利用ANSYSStructural／LS-DYNA对齿轮进行了显式动力分析,得到了该齿轮在冲击载荷作用下所受到的冲击力的值,随后进行了瞬态响应的研究,得到了齿轮在冲击载荷作用下的应力和变形。通过比较可知,冲击载荷的危害是静态载荷的数倍,证实了齿轮在该工况下必然发生断裂,为齿轮的合理设计提供了依据。     

预紧力和螺栓位置对螺栓群连接构件的影响

为研究螺栓群连接构件的力学性能,以某高速列车中较具代表性的螺栓群连接构件为研究对象,利用非线性有限元接触算法和等效外载法施加预紧力,分别对不同螺栓预紧力和不同螺栓布置位置情形下的连接构件进行仿真.通过对孔周应力的比较,得出最佳螺栓布置位置和螺栓预紧力.     

轴承预紧力对转子系统静动态特性的影响

轴承预紧力的大小直接影响到滚动轴承-转子系统的静动态特性. 综合考虑离心力和陀螺力矩效应,在Romax软件中建立了5自由度轴承-转子系统动力学模型,分析了预紧力对轴承刚度、工作接触角以及工作寿命的影响,并搭建了轴承 转子系统试验台做验证试验. 在不同轴承预紧力下,分别研究了轴承刚度、工作接触角、工作寿命、静载荷作用下轴承 转子系统的静变形以及动不平衡载荷作用下主轴系统的振动响应等,并在轴承-转子试验台上进行试验验证,得到了轴承预紧力与这些因素的关系曲线. 在此基础上,研究了预紧力对转子系统固有频率的影响,结果表明加大预紧力有助于提高系统的固有频率. 研究结果可为轴承-转子系统的设计与分析提供理论参考.     

基于改进元胞多目标遗传算法的机床主轴优化

为了进一步提高元胞遗传算法在求解多目标优化问题时的收敛性和分布性。在多目标元胞遗传算法的基础上,引入了三维空间元胞,提出了三维元胞多目标遗传算法。采用多目标基准测试函数对该算法进行了测试,并将其与目前比较流行的几种多目标遗传算法进行对比。结果表明,此种算法在收敛性和分布性上取得了更好的效果。采用以上这几种算法分别对机床主轴多目标优化问题进行了求解,相比其他几种算法,改进的多目标元胞遗传算法得到了更优的结果,说明了改进的算法在求解此问题时行之有效。     

一种利用轮辐式传感器测预紧力的高效试验机

正申请号:201310025815.0【公开号】CN103115710A【公开日】2013.05.22【分类号】G01L5/00(2006.01)I【申请日】2013.01.24【申请人】贵州航天精工制造有限公司【发明人】白玉康;谢丹贤;刘如刚;宋庆华【摘要】本发明公开了一种利用轮辐式传感器测预紧力的高效试验机,它包括底座、U型座、轮辐式数显推拉力传感器、固定座、立板、预紧套、预紧板、按钮操作箱以     

不同工况下仿生叶轮水上推进性能数值分析

研究采用蛇怪蜥甥踏水机理设计的轮-叶复合式仿生推进装置,针对实现推进性能最大化的仿生叶轮装置设计的难点,从减少叶片能量损失的角度设计了一种压水防溅型仿生叶轮结构,如何有效获取新型叶轮结构的水上推进性能,应用计算流体力学数值方法,通过构建不可压缩非稳态的N-S主控制方程,采用欧拉网格有限体积法的离散化处理方式,综合应用VOF模型和动网格技术,实现对新型仿生叶轮水上推进性能的数值模拟,着重讨论了不同转速ω和负载P下的仿生叶轮水平速度v1和水平位移s1的变化规律,研究仿生叶轮运动中压力场、速度场和气液相的分布特点,获得了转速ω和负载P对仿生叶轮水上推进性能的影响规律.仿真分析结果表明转速ω和负载P均存在一合理区间范围,使得新型仿生叶轮推进性能最优,仿真结果可为实现仿生叶轮模型水上推进性能最优提供了理论基础.     

Drilling reconfigurable machine tool selection and process parameters optimization as a function of product demand

Special purpose machines (SPMs) are customized machine tools that perform specific machining operations in a variety of production contexts, including drilling-related operations. This research investigates the effect of optimal process parameters and SPM configuration on the machine tool selection problem versus product demand changes. A review of previous studies suggests that the application of optimization in the feasibility analysis stage of machine tool selection has received less attention by researchers. In this study, a simulated model using genetic algorithm is proposed to find the optimal process parameters and machine tool configuration. During the decision-making phase of machine tool selection, unit profit is targeted as high as possible and is given by the value of the following variables: SPM configuration selection, machining unit assignment to each operation group, and feed and cutting speed of all operations. The newly developed model generates any random chromosome characterized by feasible values for process parameters. Having shown how the problem is formulated, the research presents a case study which exemplifies the operation of the proposed model. The results show that the optimization results can provide critical information for making logical, accurate, and reliable decisions when selecting SPMs.     

直线伺服6 位置环虚拟轴机床的运动学解耦

使用直线电机驱动虚拟轴机床 ,可满足高速时动态响应和提高精度的要求。如何解决 6位置环虚拟轴机床的强耦合 ,一直是虚拟轴机床伺服控制中的一个难题。为此 ,将局部结构化方法与解耦理论相结合 ,提出一种新的解耦算法 ,从理论上实现了对 6位置环虚拟轴机床的平动和转动之间的解耦     

A group decision making framework based on fuzzy VIKOR approach for machine tool selection with linguistic information

Computer numerical control (CNC) machines are used for repetitive, difficult and unsafe manufacturing tasks that require a high degree of accuracy. However, when selecting an appropriate CNC machine, multiple criteria need to be considered by multiple decision makers. In this study, a multi-criteria group decision making (MCGDM) technique based on the fuzzy VIKOR method is developed to solve a CNC machine tool selection problem. Linguistic variables represented by triangular fuzzy numbers are used to reflect decision maker preferences for the criteria importance weights and the performance ratings. After the individual preferences are aggregated or after the separation values are computed, they are then defuzzified. In this paper, two algorithms based on a fuzzy linguistic approach are developed. Based on these two algorithms and the VIKOR method, a general MCGDM framework is proposed. A CNC machine tool selection example illustrates the application of the proposed approach. A comparative study of the two algorithms using the above case study information highlighted the need to combine the ranking results, as both algorithms have distinct characteristics.     

基于机器学习的人工智能语义分析方法

针对中国移动河南公司对敏感数据的金库管控现状,设计采用机器学习的框架数据,结合挖掘算法和贝叶斯算法,并运用中文分词的原理形成人工智能语义分析方法,在对敏感操作源头进行操作时,可以有效地规范和约束行为,增强对人为访问敏感数据时的甄别及管控能力,进而为各类敏感数据提供保护措施和精准的前提要素。     

混凝土结构温度内力数值分析

为研究混凝土结构的温度效应,利用ANSYS对混凝土框架、框架-剪力墙和剪力墙等结构在温度变化作用下的变形特点和内力分布规律进行系统分析.对具有不同纵向长度、楼层数和建筑体形特征的结构分别建立计算模型,在假设建筑物内外无温差和有温差两种温变条件下进行计算分析,从中得到各种结构温度变形和内力分布的基本规律,其主要结论对结构工程师具有实用价值.     

Applying an improved failure mode effect analysis method to evaluate the safety of a three‐in‐one machine tool

Straighteners are commonly used in the field of plate straightening. With the shortage of industrial land, an increasing number of straightener manufacturers integrate uncoilers, straighteners, and feeders, which represent a three‐in‐one machine tool. The tool's functions are complex; many factors affect its reliability and performance, including the problems of equipment itself and human errors. To improve the reliability of this machine, it is necessary to identify the main failure modes and causes. The risk assessment of using the conventional failure mode and effects analysis (FMEA) presents several issues. Thus, multiple methods have been proposed to improve the robustness and applicability of the FMEA. Herein, an improved FMEA, which combines fuzzy set and entropy evaluations is utilized to assess the three‐in‐one machine tool. In the method, the fuzzy set method is used to quantify the evaluation index. The information entropy and expert evaluation method are used to determine the weight between the indexes. From this study, human operation errors accounted for over 55% of the risks of machine malfunctions. By evaluating failure modes, a few countermeasures to reduce human operation errors can be proposed. By improving the human machine interface design and ergonomic job design and providing adequate training, human errors can be reduced and the reliability of three‐in‐one machine tools can be improved.     

基于机器学习的入侵检测方法实验与分析

入侵检测系统(IDS)是保障信息安全的重要手段。分析了机器学习应用于网络连接级的异常检测模型的过程,然后建立了异常检测系统原型,以验证此方法用于IDS的可能性及所能达到的性能。实验以DARPA网络数据为例,对数据的特征进行了分析、选取及构造,并针对多种情况进行了测试。实验结果表明,该IDS系统具有很好的检测性能。最后对结果进行了分析,并得出了几个有用的结论。     

Computer-supported information requirement analysis tool based on novel methodology for analysing CIM information requirements

A computer-supported information requirement analysis tool (COMSIRA) has been developed for an existing novel methodology (integration-based requirement analysis methodology (IBRAM)); in order to capture and represent the approach of experienced analysts studying the enterprise-wide CIM information requirements. This paper introduces the methodology and describes the operational aspects of COMSIRA, which is a user friendly CASE tool that can be used by people with little prior computer experience for the establishment of requirements. Systems analysts can use it for analysing and modelling the CIM environment for both the static and dynamic requirements of a CIM implementation within small and medium-sized enterprises (SMEs).     

多传感器融合的数控机床热误差回归建模新方法

热误差对机床的加工精度影响很大,高性能的补偿系统依赖于多传感器融合建立的三维模型的精度、鲁棒性和合适的温度进行反馈输入。本文使用温度与位移传感器的模糊聚类进行温度分类,基于评价模型比对分析最优的温度分类,从每个分类中选择具有代表性温度作为候选温度。归纳试验数据,使用分段逆回归SIR模型进行热误差建模,SIR模型将高维前移回归问题转化为多个一维的回归问题,并且进一步消除了候选温度之间的耦合。热误差试验表明,SIR模型具有泛化能力强、预测精度高及鲁棒性好的特点,能够准确地描述多种典型工况条件下的实际热误差特性。