运载火箭主动段自适应增广控制

针对运载火箭上升段在复杂飞行环境、大不确定性干扰和振动等因素的影响下，传统PID控制方法难以满足高品质控制需求的问题，进行了自适应增广控制(AAC)方法研究，以实现对运载火箭姿态的精确控制。在深入分析自适应增广控制系统整体构架的基础上，通过标称PID控制器设计与基于粒子群优化(PSO)的数字滤波器设计实现了刚体控制及对弹性振动的抑制；继而针对大范围干扰、不确定性和由于滤波器切换产生的弹性振动影响，设计了在线调整算法自适应调节PID控制增益，并对其工作机理与参数设计原则进行研究；然后设计干扰补偿回路和主动减载回路以减小内外扰动、弹性振动和风载荷影响；最后在弹性振动、风干扰和参数不确定性等因素同时作用的状态下进行仿真分析，验证了自适应增广控制系统能够有效应对运载火箭主动段复杂飞行环境的影响，大幅度提升综合控制性能，具有理论研究意义与工程应用价值。     

基于图像识别的机械振动信号特征提取与寿命预测方法研究

滚动轴承作为许多机械设备的关键组件,被广泛应用于机械制造、航空航天等领域,其健康状态直接影响了相应设备的剩余寿命,因此在设备故障预测与健康管理(Prognostics and Health Management, PHM)领域,滚动轴承寿命预测具有很高的研究价值。目前基于数据驱动的轴承寿命预测方法主要利用特征提取并构造健康因子(Health Indicator, HI),然而在这一过程中特征的选择与融合依然依赖于专家先验知识,并且健康因子也很难从复杂的时序数据中进行提取。因此,提出了一种新型的数据驱动寿命预测算法,在特征提取方面,通过连续小波变换(Continuous Wavelet Transform,CWT)将传感器振动信号转换为时频谱图,再通过深度残差网络(Deep residual network, ResNet)结合时空卷积网络(Temporal Convolutional Network, TCN)将时频谱图中的时域频域特征构造成为健康因子,最后完成剩余寿命预测。本研究在PRONOSTIA数据集上与现有的数据驱动算法进行了对比,证明了该算法可以更准确地完成剩余寿命预测。     

Near-wall topological patterns and flow structures over a simplified Danaus plexippus model

Studies on the high-lift mechanisms of butterfly gliding flights shed light on the design of the micro air vehicles. The flow field around a simplified Danaus plexippus model is investigated using the hydrogen bubble visualization and the Particle Image Velocimetry (PIV) techniques. There are three near-wall topological patterns with different Angles of Attack (AoAs): the separation bubble, the Leading-Edge Vortex (LEV) and the high AoAs flow. For the separation bubble pattern, two saddles and two foci form in the middle of the model. The features of the LEV pattern are the leading-edge separation lines. The topological characteristics of the separation lines are changed by the interaction between the LEV and the Wing-Tip Vortex (WTV). For the high AoAs flow pattern, four unstable foci are found at the forewing and the hindwing respectively. The angle between the trajectory of the WTV and the model increases with increasing AoA even though the slope of the WTV angle versus AoA curve declines at the moderate AoAs.     

Latitudinal distribution of solar coronal active regions

We studied the cyclic evolution of the latitudinal distribution of solar coronal active regions based on daily images from SOHO EIT for the period 1995–2017. Fully automated software was used, which included the following steps: initial preparation of images in the data series, normalization of histograms and correction of limb brightening, segmentation of images using threshold intensity values obtained from their histograms, scanning of segmented images in heliographic coordinates and obtaining profiles of latitudinal distribution of coronal active regions for each image of the data series. From the output data, we obtained a temporary change in the latitudinal distribution profiles and the migration of activity centers on the solar disk. From the period of minimum activity to the next minimum in both hemispheres, activity centers begin to migrate from high latitudes towards the equator. At the same time, the general center of activity repeatedly changes the direction of migration. The latitudinal distribution of the so-called presence factor of coronal active regions closely resembles the magnetic butterfly diagram, which proves their direct causal relationships. Variations in the presence factor of coronal active regions are correlated with cyclic variations in the sunspot daily numbers.     

一种基于系留无人机的图像遥测系统设计

针对海上船舶甲板的监控需求，本文提出了一种基于系留无人机的图像遥测系统设计方法，即通过系留无人机上的图像采集装置对被监控目标进行视频信号实时采集、压缩，再经过遥测装置的编码、调制、放大后由天线进行辐射，最后由数十公里外的遥测接收机完成接收、解调、解码，可实时显示船舶甲板图像信息。文中介绍了系统的软硬件组成、关键设备的设计方法、综合性能的分析，对相关图像遥测技术应用有一定参考意义。     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

Formation flying reconfiguration manoeuvres via environmental forces in highly elliptical orbits

A study on reconfiguration manoevres applied to a tetrahedral formation in highly elliptical orbits is proposed, by using a propellantless solution. The manoeuvring strategy consists in exploiting certain environmental forces, specifically those provided by solar radiation pressure and atmospheric drag, by actively controlling the satellites’ attitudes. Through inverse dynamics particle swarm optimization the optimal attitudes required for the manoeuvres are evaluated, whereas the configuration’s evolution is simulated by a high-fidelity orbital simulator. The goal of the reconfiguration problem is to find an optimal control in order for the four spacecraft to reach a desired configuration in a specified portion of orbit, where the desired configuration is evaluated by a shape and size geometric parameter. By increasing the manoeuvring time and the satellites’ area to mass ratio, all the case studies considered are successfully verified.     

PVC糊树脂对交联PVC泡沫塑料的影响

通过水煮发泡制备交联聚氯乙烯泡沫塑料,讨论了聚氯乙烯(PVC)糊树脂对泡沫制备过程中经制糊、模压和发泡工艺得到的产物的影响,研究了PVC糊树脂对制备的交联PVC泡沫压缩性能的影响.结果表明:制备交联聚氯乙烯泡沫塑料适宜的糊黏度是4～9 Pa·s;PVC糊树脂的K值较大或水萃取液pH值呈碱性可有效防止模压过程中PVC的降解;PVC糊树脂的水萃取液pH值呈碱性可催化发泡反应,有利于得到低密度泡沫且缩短发泡时间;随着其K值增加,制备的泡沫压缩强度增大,但是K值过大时,制备的泡沫泡孔较大,压缩强度反而降低,适宜的K值为70～80.     

高密度烃燃料雾化特性试验

采用试验手段研究了高密度烃燃料在直射式喷嘴情况下的雾化规律,采用数字图像处理技术,使用粒子图像测速系统（PIV）对其在横向高温气流中形成的喷雾场进行图像测量和分析。初步研究了气流温度、油压、气压与气流速度对高密度烃燃料雾化特性的影响,以及射流与喷嘴距离对喷雾粒子索太尔平均直径（SMD）的影响。试验结果显示：气流温度和油压的增加有助于提高高密度烃的雾化效果。在研究气流速度对其影响时,要考虑加热气流蒸发产生的影响,在雾化初始阶段速度因素占主导地位,而在下游距离喷嘴50~75mm间的某一位置开始,蒸发因素将起到主要作用。通过数值计算与实验比较,进一步说明了高温气流蒸发作用在颗粒二次雾化中的重要性。研究结果为优化设计高密度烃燃料发动机燃烧室提供依据。