径向圆跳动误差的最小二乘评定数学模型和微机数据处理

用传统的测量方法只能得到被测零件的径向圆跳动误差的近似值。为了得到该项误差的准确值，需要研究新的测量方法。建立了径向圆跳动误差最小二乘评定数学模型，并编制了高级语言数据处理程序。在万能工具显微镜上获得了采样数据，给出了计算结果。     

采用DSG技术实现零件模型分解

针对回转体和箱体类零件模型,应用分解性实体几何技术实现零件设计模型到制造模型的有序分解,介绍了基于特征树模型的两个关键算法:宽度优先和深度优先搜索,以完成面向特征加工过程的空间和时间域内的制造过程规划.最后用一个详细的算例进一步陈述零件模型分解技术.     

Jobshop问题中动画仿真模型的自动生成系统

对于给定目标,仿真过程可大致分为仿真建模,程序实现,仿真结果的统计分析三大部分,其中仿真建模是最基础的,关系整个仿真成败的环节,如果能够在仿真模型完成后自动生成相应的仿真程序,不中大大减少了工作量,还可使工作者集中精力于仿真建模,使模型更准确,更优化,本文以Ｊｏｂｓｈｏｐ问题为例,给出了一中基于ＳＩＭＡＮ／ＣＩＮＥＭＡ软件的动画仿真程序自动生成系统,但该系统整体设计思想并不局限于ＳＩＭＡＮ／ＣＩＮ     

大气闪烁对近似无衍射激光通信系统的影响

在近似无衍射激光通信系统中,大气湍流的作用导致接收端光强起伏不定,这将对通信系统的误码率产生影响.以光强起伏的概率分布为基础,忽略系统中的其他噪声,推导出折射率结构常数、通信距离和激光波长等影响因素与误码率的关系式.通过计算机模拟,研究了误码率随折射率结构常数的变化规律,讨论了一定湍流强度下通信距离和激光波长对误码率的影响,并以10-9为误码率标准,确定了通信距离的允许范围.结果表明,合理地选择天气和日照条件、减小通信距离以及选择长波长的激光器可以减弱大气湍流对误码率的影响.      

基于离散数据点的变壁厚叶身参数化设计

在原始截面离散数据点的基础上,给出了面向工程实际的中弧线几何造型方法和基于离散数据点的内形曲线参数化方法;深入分析了UG(Unigraphic)系统参数化造型的实质;给出了可行的参数化方案;结合面向对象的思想和创成式的建模方式,实现了变壁厚叶身参数化设计.该模块基于UG/OpenAPI接口,采用即时记录数据点和标记回溯点的方式,在交互中可以实时动态修改,达到"所见即所得"的效果,并在实际应用中得到有效验证.      

驱动轮结构参数对月球车牵引性能影响研究

研究在月球表面环境下月球车的牵引通过性能,对保证其正常探测工作具有重要意义.根据牵引性能的评价指标,在模拟月壤-车轮土槽测试系统上对不同结构参数的驱动轮牵引性能进行对比试验.结果表明,当增大驱动轮宽度和直径时,其挂钩牵引力和效率系数都呈增大趋势;增大驱动轮的轮刺高度,挂钩牵引力增大;当滑转率小于20%时,效率系数随着轮刺高度的增大而增大,而当滑转率大于20%时,效率系数随着轮刺高度的增大而减小;增大驱动轮轮刺密度时,其挂钩牵引力和效率系数随之先增大后减小.      

不确定载荷下的桁架结构拓扑优化

对带有不确定扰动载荷的桁架结构拓扑优化问题进行了研究.将不确定载荷表示成有界凸集,从而把不确定性问题转化为一个确定性问题.构造了凸集载荷下以体积为约束的柔度最小化模型,该优化模型的实质是在高维椭球内计算最大柔度最小问题.由于采用传统优化模型存在计算上的困难,对凸集载荷进行了数学处理,并据此构造了半定规划形式的优化模型以便求解.优化结果相对于给定载荷的刚度虽然略低,但对不确定的扰动载荷却具有一定的承载能力.算例表明通过半定规划法构造的考虑扰动载荷作用下的优化结果鲁棒性较佳,结构形式更接近于实际工程结构.     

静稳定裕度对飞翼布局的影响研究

减小配平损失对于提高飞翼布局升阻比和提升飞行控制能力具有重要意义,因此基于离散伴随优化方法研究静稳定裕度对跨音速飞翼布局减阻优化的影响,分别开展10%,0%,-10% 三种静稳定性设计工况的优化研究。采用自由变形（FFD）方法对非结构表面网格进行参数化,以FFD 控制点为设计变量,通过求解流场和伴随方程得到灵敏度信息;采用序列二次规划SQP 算法获得控制点位移的梯度,然后经过多轮迭代得到优化构型。结果表明：在几何厚度和力矩配平的约束下,离散伴随优化方法可以显著提升飞翼布局的最大升阻比,三种工况下最大升阻比提高都在8% 以上;随着静稳定性裕度减小,定升力系数优化的巡航升阻比增量有所减小,当静稳定裕度为10% 时巡航升阻比提高了5.08%。     

Countermeasure Against Regenerative and Forced Chatter of Flexible Workpieces in Milling Processs Using Bi-directional Excitation

A novel extended methodology for chatter suppression in milling process by applying external forced vibrations to the workpiece in two orthogonal directions which are the feed and cross-feed directions.Both the regenerative and forced chatter suppression during the milling process of flexible workpieces are investigated.Here,the workpiece is subject to a sinusoidal periodic force in the feed direction to disrupt the regenerative effect.Additionally,to minimize the forced chatter,the workpiece is subject to the periodic excitation force in cross-feed direction.This force is proportional to the magnitude of the estimated cutting force in cross-feed direction and has a phase opposite to the cutting force to minimize the vibration amplitudes.The effectiveness of the proposed method is evaluated numerically and experimentally,for the spindle speed located in both the local minima and local maxima of the stability lobe diagram.The numerical simulations indicate significant suppression effect in terms of vibration amplitudes,resulting in suppression of both the regenerative chatter and the forced chatter.Experiments were conducted by using a workpiece-mounted active stage composed of flexure hinges and driven by piezoelectric actuators.The experimental results agree qualitatively with the numerical simulations.The proposed method indicates a remarkable vibration reduction effect for both regenerative and forced chatters.     

Variational Mode Decomposition for Rotating Machinery Condition Monitoring Using Vibration Signals

The failure of rotating machinery applications has major time and cost effects on the industry.Condition monitoring helps to ensure safe operation and also avoids losses.The signal processing method is essential for ensuring both the efficiency and accuracy of the monitoring process.Variational mode decomposition(VMD)is a signal processing method which decomposes a non-stationary signal into sets of variational mode functions(VMFs)adaptively and non-recursively.The VMD method offers improved performance for the condition monitoring of rotating machinery applications.However,determining an accurate number of modes for the VMD method is still considered an open research problem.Therefore,a selection method for determining the number of modes for VMD is proposed by taking advantage of the similarities in concept between the original signal and VMF.Simulated signal and online gearbox vibration signals have been used to validate the performance of the proposed method.The statistical parameters of the signals are extracted from the original signals,VMFs and intrinsic mode functions(IMFs)and have been fed into machine learning algorithms to validate the performance of the VMD method.The results show that the features extracted from VMD are both superior and accurate for the monitoring of rotating machinery.Hence the proposed method offers a new approach for the condition monitoring of rotating machinery applications.