月球表层采样样品智能确认方法

表层采样是月球采样探测的重要方式，样品智能确认有助于提升工作效率与复杂问题处理能力。结合月球表层采样铲挖工作过程，分析了铲挖过程中臂载相机图像的特点，模仿有人参与识别过程，提出了层次解耦的月球样品智能识别流程，利用深度学习方法构建了一类深度卷积识别网络，完整地描述了图像、特征、标记在网络中的正反传递关系，并在月球表层采样地面试验中进行了验证，结果表明该方法对不同光照、不同背景、不同过程、不同形态的样品，具有较好的泛化识别能力，误识别率优于8.1%，平均单幅识别时间约0.7 s。     

智能结构动力系统控制器设计和结构优化的综合分析

通过由两个压电作动器控制的空间桁架,将最优控制问题和结构中杆件截面积动态优化相结合,综合分析了二者的混合优化问题.计算结果表明,在结构动态响应特性不变的条件下,结构重量和控制需求均有显著下降.      

低温推进剂加注液位信号智能处理技术研究

低温加注系统是运载火箭发射场地面支持设备的重要组成部分,包括低温介质的储存、运输、供给、控制以及安全等内容。由于低温推进剂本身存在低温沸腾、易挥发的特性,其加注过程十分复杂,为满足新一代运载火箭推进剂精准的加注要求,需要实时准确监测加注过程中贮箱内的液位高度。本文针对火箭地面加注过程的液位信号数据,对其三角波电压和线性波电压的特征进行分析、提取,基于BP（Back Propagation,反向传播）神经网络算法完成对不同加注状态的识别检测,并应用于传感器节数判别,优化了液位计算算法,降低了节数人为干预需求,提高了液位测量准确性。经实验测试验证,该方法可有效识别低温加注状态,识别准确率达到90%以上,用于液位信号处理中可显著提升液位高度计算的准确性。     

新一代GNSS接收机的智能跟踪状态评估技术

新一代全球导航卫星系统的接收机需要根据用户所处环境,自适应地调整接收机内部参数以达到最稳健的导航效果。这就要求接收机在运行过程中通过评估跟踪状态去检测和分析用户场景。基于对传统接收机控制系统缺陷的分析,提出了智能接收机的概念、特点及系统框架;在此基础上设计、分析接收机的智能跟踪状态评估算法;最后通过仿真验证了所设计的算法可以有效地识别场景及场景间的切换。     

基于LabVIEW的电动舵机智能检测系统设计与实现

以LabVIEW为应用程序开发平台设计了电动舵机智能检测系统,该系统改变原有手动测试为智能测试,自动化程度高,多种信号综合,以上限264M的PXI总线型高性能计算机为控制核心,采用信号集成和转换技术,实现不同性质信号的综合变换与处理,测试项目和准确度满足电动舵机的测试要求.     

High-precision shape approximation low-thrust trajectory optimization method satisfying bi-objective index

The shape approximation method has been proven to be rapid and practicable in resolving low-thrust trajectory; however, it still faces the challenges of large deviation from the optimal solution and inability to satisfy the specific flight time and fuel mass constraints. In this paper, a modified shape approximation low-thrust model is presented, and a novel constrained optimization algorithm is developed to solve this problem. The proposed method aims at settling the bi-objective optimization o...     

智能气囊缓冲器在航天器回收着陆中的应用探讨

文章提出将智能气囊技术应用于飞船返回舱座椅作为返回落地缓冲,设计了智能气囊缓冲器方案,并论述了智能气囊缓冲器在飞船座椅上应用的可行性。与胀环式机械缓冲器比较,智能气囊保持了较高的缓冲效率,同时可使航天员受到的冲击过载特性曲线更加平坦,从而提高航天员着陆的安全性和舒适性。     

Towards intelligent design optimization: Progress and challenge of design optimization theories and technologies for plastic forming

Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent (smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling, multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear, high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things (IoT), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm, this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process.     

智能化传感器综述

本文简要介绍了智能化传感器的基本概念及国内外发展动向.在介绍智能化传感器的类型及主要组成部分的基础上,还以实例说明智能化传感器在航空、航天技术、工业控制、机器人等方面的应用.最后对智能化传感器的优缺点进行了分析,展望了智能化传感器在我国的发展.     

航空发动机智能制造生产线构建技术研究

结合航空发动机制造生产线特点,研究了智能制造的特征及要素,设计了面向航空发动机的智能制造生产线架构,并阐述了实施内容、关键技术及实现方法,为智能制造技术在航空发动机制造企业以及装配制造业应用提供了重要参考.