Design of face-hobbed spiral bevel gears with reduced maximum tooth contact pressure and transmission errors

The aim of this study is to define optimal tooth modifications, introduced by appropriately chosen head-cutter geometry and machine tool setting, to simultaneously minimize tooth contact pressure and angular displacement error of the driven gear (transmission error) of face-hobbed spiral bevel gears. As a result of these modifications, the gear pair becomes mismatched, and a point contact replaces the theoretical line contact. In the applied loaded tooth contact analysis it is assumed that the point contact under load is spreading over a surface along the whole or part of the ’’potential’’ contact line. A computer program was developed to implement the formulation provided above. By using this program the influence of tooth modifications introduced by the variation in machine tool settings and in head cutter data on load and pressure distributions, transmission errors, and fillet stresses is investigated and discussed. The correlation between the ease-off obtained by pinion tooth modifications and the corresponding tooth contact pressure distribution is investigated and the obtained results are presented.     

复合材料帽形加筋结构稳定性研究

建立了复合材料帽形加筋结构的参数化有限元模型,给出了两种进行层板结合处的模拟计算方法,通过计算得到了模型的屈曲载荷并总结了加筋结构几何参数对结构稳定性的影响,给出了模型的收敛性分析,对比了模型网格密度对于计算结果的影响,找到最佳的网格密度,提高了模型计算的效率和准确性,为实际的结构设计提供了重要参考,为结构分析提供了依据。     

民机结构维修大纲抽样检查原则与方法研究

民机结构维修中的抽样检查是保证飞机持续适航的关键措施。结构抽样检查是为了掌握同一时期下线飞机的结构损伤情况,以便更好地修订维修计划。针对民机结构维修的抽样是非随机抽样的特点,本文研究了结构维修抽样的原则,结合空客A320抽样经验,给出了我国自主设计大飞机结构维修抽样准则和抽样的具体步骤。     

基于传动误差和齿面印痕控制的弧齿锥齿轮小轮加工参数的设计(英文)

This paper proposes a new approach to design pinion machine tool-settings for spiral bevel gears by controlling contact path and transmission errors. It is based on the satisfaction of contact condition of three given control points on the tooth surface. The three meshing points are controlled to be on a predesigned straight contact path that meets the pre-designed parabolic function of transmission errors. Designed separately, the magnitude of transmission errors and the orientation of the contact path are subjected to precise control. In addition, in order to meet the manufacturing requirements, we suggest to modify the values of blank offset, one of the pinion machine tool-settings, and redesign pinion ma- chine tool-settings to ensure that the magnitude and the geometry of transmission errors should not be influenced apart from minor effects on the predesigned straight contact path. The proposed approach together with its ideas has been proven by a numerical example and the manufacturing practice of a pair of spiral bevel gears.     

螺旋型喷嘴液滴分布特性及液滴直径经验公式的拟合

螺旋型喷嘴是压力式喷嘴的一种,它能提供细密的水雾,在工程上具有广泛的用途.笔者分析了几种常用的表征液滴尺寸的参数,用因次分析的方法建立了螺旋型喷嘴液滴直径的准则关系式,通过实验研究了TF6喷嘴的雾化液滴几种常用的直径随喷雾压力的变化规律,用最小二乘法回归了TF型喷嘴雾化粒子的几种直径(D0.1、D0.5、D0.9、D32)的经验公式.     

柔性杆子杆模型参数的遗传算法优化求解

研究了应用实数型的遗传算法解决柔性机器人子杆法建模中,子杆模型参数的优化求解问题.子杆模型参数形成高度非线性的方程组,它的求解是子杆法能否实现的关键.普通的牛顿迭代法及其变形,要求初始向量足够靠近解,一些所谓大范围收敛的算法又有方程组的Jacobian矩阵非奇异等要求,在此都难以应用.本文基于遗传算法的解法可求得模型参数的最优解,实例仿真显示了这一方法的可行性和高效率.      

双立尾/三角翼布局的立尾抖振研究

在北航的风洞中进行了双立尾-三角翼布局的立尾抖振实验,目的是研究立尾抖振产生的原因.主要采用了激光测振仪测立尾加速度和动态压力传感器测立尾表面的动态压力的实验方法.实验结果表明在旋涡破裂以后,立尾上就会产生强烈的抖振.抖振是由立尾上表面压力的周期性脉动造成的.对机翼和立尾表面的压力频谱分析表明,立尾上的压力脉动来源于机翼前旋涡破裂流中的螺旋波.对于本实验使用的模型来说,当机翼迎角α=0°~20°范围,由于流动是附着流和涡流,所以立尾没有明显抖振;当机翼迎角在α=20°~56°范围,立尾处在破裂涡流的范围,立尾抖振明显,并且抖振强度在35°~50°之间达到最大.因此,三角翼破裂涡流中的螺旋波正是双立尾产生抖振的主要原因.     

Investigation on the interface damage in drilling low-stiffness CFRP/Ti stacks

Carbon fiber reinforced plastic and titanium alloy (CFRP/Ti) stacks have been widely used as aerospace structures because of their excellent combination of physical properties. Interface damage caused by interface gaps, significantly different from that of metal/metal stacks, is a common problem in the through-hole drilling of CFRP/Ti stacks with low stiffness. In this study, a force–deformation coupling model was developed to further examine the formation mechanism and the control method of interface damage. Firstly, the coupling model was built considering the interaction between the thrust force and the deformation. To solve this model, a numerical method was proposed in which specific cutting coefficients were calibrated using only the thrust force of rigid stacks. Secondly, drilling experiments were performed with different feed rates and bending stiffness. Experimental results indicate that interface damage mainly includes interlayer chips and surface damage of CFRP layers. The surface damage, which is irreparable, is caused by the rotary extension of metal chips along the interlayer gap. Thirdly, variations of the interface gap were calculated with the coupling model that had been verified by measured thrust forces. The damage area was found to have a linear dependence relation with the interlayer gap. However, in conditions of large gap sizes, the interface damage areas increased with the interlayer gap at high feed rates, while decreasing slightly at low feed rates. This phenomenon was satisfactorily explained by the presented model. Finally, a method was proposed to determine the appropriate pressure exceeding which no interlayer damage will occur. Additional drilling experiments proved the method effective. This study leads to further understanding of the forming mechanism of interlayer damage and of selecting appropriate parameters in drilling low-stiffness composite/metal stacks.     

Classification of solar wind structures and intense geomagnetic storm alarms with self-organizing maps

Intense geomagnetic storms (D_st < −100 nT) usually occur when a large interplanetary duskward-electric field (with Ey > 5 mV m⁻¹) lasts for more than 3 h. In this article, a self-organizing map (SOM) neural network is used to recognize different patterns in the temporal variation of hourly averaged Ey data and to predict intense storms. The input parameters of SOM are the hourly averaged Ey data over 3 h. The output layer of the SOM has a total of 400 neurons. The hourly Ey data are calculated from solar wind data, which are provided by NSSDC OMNIWeb and ACE spacecraft and contain information on 143 intense storms and a fair number of moderate storms, weak storms and quiet periods between September 3, 1966 and June 30, 2002. Our results show that SOM is able to classify solar wind structures and therefore to give timely intense storm alarms. In our SOM, 21 neurons out of 400 are identified to be closely associated with the intense storms and they successfully predict 134 intense storms out of the 143 ones selected. In particular, there are 14 neurons for which, if one or more of them are present, the occurrence probability of intense storms is about 90%. In addition, several of these 14 neurons can predict big magnetic storm (D_st  −180 nT). In summary, our method achieves high accuracy in predicting intense geomagnetic storms and could be applied in space environment prediction.