直升机超临界尾传动轴限幅减振器非线性动力学特性研究

直升机超临界尾传动轴在跨临界转速时会产生剧烈的振动。限幅减振器是专门针对尾传动轴跨临界减振问题设计的一种复合式减振器。限幅减振器与尾传动轴组成的系统具有摩擦、碰撞等强非线性特征,动力学特性异常复杂。为揭示限幅减振器工作机理并指导减振器设计,建立了具有双间隙结构的限幅减振器与尾传动轴系统的弹簧-质量-阻尼等效模型。分别基于直接时间域积分和时频变换谐波平衡（Harmonic Balance Method with Alternating Frequency-Time Domain Technique）+数值延拓（Numerical Continuation）两种方法对控制方程进行了求解。计算结果表明,限幅减振器存在无作用、正常减振、异常减振、限位四种工作状态。其中,限位状态是针对故障工况下尾传动轴进行的临时限位保护。此外,进一步研究了减振器参数对减振和限位效果的影响,得到了传动轴与碰摩环之间间隙、碰撞刚度以及临界摩擦力对限幅减振器减振效果的影响规律。发现存在最优临界摩擦力,且最优临界摩擦力与传动轴不平衡量等有关。同时限位状态下,通过增加碰摩环与底座之间的碰撞刚度可以减小限位幅值,但也会产生...     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

Investigation of the annealing texture evolution in hafnium

This article presents a study of the evolution of the annealing texture in hafnium, as measured by electron backscattering diffraction patterns (EBSPs). It was found that the annealing texture of asreceived extruded rod depended on the annealing temperature. After low-temperature recrystallization, the deformation axis was parallel to or and the basal planes were approximately parallel to the deformation axis. These orientations were deduced by the position of the points in the standard stereographic triangle used to produce the inverse pole figure. As the annealing temperature was raised to 1700 °C, the direction parallel to the rolling direction changed to and the grain size increased. It appeared that the increase in grain size occurred by a process of abnormal grain growth, and this abnormal grain growth appeared to be the cause of the change in the texture. Texture was also examined in samples that had been warm rolled to thickness reductions between 10 and 90 pct and then annealed at 1700 °C. In these samples, the main feature of the texture was that the basal plane became parallel to the rolling plane as the amount of rolling increased. The maximum grain size was observed in samples that had been rolled to a reduction in thickness of 50 pct.     

Molecular dynamics simulation on flow behavior of nanofluids between flat plates under shear flow condition

Molecular dynamic model of nanofluid between flat plates under shear flow conditions was built. The nanofluid model consisted of 12 spherical copper nanoparticles with each particle diameter of 4 nm and argon atoms as base liquid. The Lennard–Jones (LJ) potential function was adopted to deal with the interactions between atoms. Thus, the motion states of nanoparticles during the process of flowing were obtained and the flow behaviors of nanofluid between flat plates at different moments could be analyzed. The simulation results showed that an absorption layer of argon atoms existed surrounding each nanoparticle and would accompany with the particle to move. The absorption layer contributed little to the flow of nanoparticles but much to the heat transferring in nanofluids. Another phenomenon observed during shear flowing process was that the nanoparticles would vibrate and rotate besides main flowing with liquid argon and these micro-motions could strengthen partial flowing in nanofluids.     

Modeling and Neuro-Fuzzy adaptive attitude control for Eight-Rotor MAV

This paper focuses on modeling and intelligent control of the new Eight-Rotor MAV which is used to solve the problem of low coefficient proportion between lift and gravity for Quadrotor MAV. The dynamical and kinematical modeling for the Eight-Rotor MAV was developed which has never been proposed before. Based on the achieved dynamic modeling, two types of controller were presented. One type, a PID controller is derived in a conventional way with simplified dynamics and turns out to be quite sensitive to sensor noise as well as external perturbation. The second type controller is the Neuro-Fuzzy adaptive controller which is composed of two type-II fuzzy neural networks (TIIFNNs) and one PD controller: The PD controller is adopted to control the attitude, one of the TIIFNNs is designed to learn the inverse model of Eight-Rotor MAV on-line, the other one is the copy of the former one to compensate for model errors and external disturbances, both structure and parameters of T-IIFNNs are tuned on-line at the same time, and then the stability of the Eight-Rotor MAV closed-loop control system is proved using Lyapunov stability theory. Finally, the validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of Neuro-Fuzzy adaptive controller performs very well under sensor noise and external disturbances, and has more superiority than traditional PID controller.     

基于多目视觉的变形钢板三维测量方法

提出了一种使用4个相机测量变形钢板三维形状的方法;在没有纹理的钢板上画一些点,使用4个相机同时拍摄钢板;利用边缘检测算法找出钢板的边缘,利用特征点提取算法提取出4个图像中钢板上的特征点,并找到4个图像上精确的特征点匹配关系,然后测量出这些特征点的三维点;最后,以这些三维点为种子点向外区域增长,从而得到钢板的三维形状;实验对变形钢板进行三维测量,得到了钢板的精确的三维形状,结果验证了该方法的有效性和可行性。     

VC和MATLAB混合编程方法在迷彩斑块设计中的应用

通过一个迷彩斑块设计实例,阐述VC和MATLAB的混合编程方法在迷彩设计中的应用。使用MATLAB函数调用图像处理工具箱,创建COM接口,从而实现VC＋＋调用该COM接口,并对返回结果进行处理。实现对输入的背景图像进行处理,获得图像的边缘轮廓,为迷彩的斑块设计提供依据。既能充分利用成熟的函数库加快软件开发,成功提取到背景的较闭合边缘,又能保证良好的用户界面及性能。     

基于集对分析的保障能力薄弱环节改进模型研究

确定保障能力薄弱环节对提高部队保障能力至关重要,目前保障能力薄弱环节确定有指标评估得分法和权重法两种方法,两种方法均存在一定的片面性。针对存在的问题,提出一种基于指标裕度空间和权重的求指标薄弱度的方法查找、确定保障能力薄弱环节,并且将集对分析的思想应用到指标优化和指标裕度空间的分析求取上,使指标薄弱度更加精确。最后结合某基层一级保障单位进行实例,运用Matlab软件仿真模型,进行保障能力指标薄弱度分析,并与目前存在的两种方法对比分析,实践证明所提出的方法更适用于保障能力薄弱环节的确定。     

视频质量客观评估方法分析

文章简单介绍了视频监控系统的应用,指出了视频质量主观评估的缺点,并按不同的分类分析了常用的视频质量客观评估方法,在此基础上探索了一种视频质量无参评客观估方法的思路。     

雷达抗干扰性能评估指标分析与测试平台设计

复杂电磁环境下雷达抗干扰性能外场实验通常具有复杂度高、设备代价高昂的问题。通过分析雷达电磁环境组成和相关评估指标,在综合一系列雷达对抗想定的基础上,提出了雷达对抗性能测试系统设计方案。该系统利用高速DSP和ARM终端显示控制灵活实现雷达干扰样式选择和参数设置。有效地解决了雷达状态信息采集、回波信号实时模拟以及战场环境想定的显控终端控制。研究了多种性能评估指标的具体测试方法,分析了影响干扰效果的关键性因素。结合具体雷达设备进行了雷达抗干扰半实物仿真实验,实验和数据处理结果证明了测试方法的有效性和可行性。该方法为解决有限设备条件下雷达抗干扰性能评估、雷达系统改进提供了参考依据。