倒锥面高层玻璃幕墙清洗机器人设计

为满足倒锥面高层玻璃幕墙清洗机器人对小质量、高可靠性、高安全性的要求,提出了运动驱动分散配置、主运动与辅助运动一体化、主运动柔性驱动的机器人结构设计原则;针对具体建筑结构设计了完备的清洗机器人系统,讨论了机器人对作业对象遍历运动和吸附、清洗功能的实现方法;分析了机器人系统对建筑结构误差的适应能力,证明了柔性驱动结构的可行性.在上述基础上开发了倒锥面高层玻璃幕墙清洗机器人系统,并进行了现场试验,证明了系统的实用性和可靠性.该系统已成功应用于机场指挥塔幕墙的清洗作业.      

基于应用识别的P2P蠕虫检测

对等网中基于漏洞传播的P2P蠕虫是严重的安全威胁.根据P2P蠕虫的传播特点,提出了一种P2P蠕虫检测方法PWD (P2P Worm Detection).PWD主要由基于应用识别技术的预处理和基于未知蠕虫检测技术的P2P蠕虫检测2部分组成,改进了干扰流量的识别和过滤规则,提出了P2P蠕虫检测规则,并引进博弈论的研究方法讨论了检测周期的选取问题.仿真结果和局域网环境下的实验结果都表明,PWD是检测P2P蠕虫和遏制其传播的有效方法.      

基于人工智能方法的传感器故障诊断技术

在液体火箭发动机地面试验过程中,传感器的失效率远高于发动机部件、组件的故障率,因而提出了采用基于人工智能的方法对传感器的故障进行检测与诊断.本文对基于人工智能方法用于传感器故障检测与诊断的特点进行了分析,并分别应用BP神经网络和自适应神经模糊推理系统（ANFIS）对某次传感器的故障进行检测.结果证明基于人工智能的方法稳定可靠,具有良好的工程应用前景.     

发动机生产加工中质量控制界限的优化

以两类错误损失费用最小为目标,对现行发动机零组件加工质量控制中以x±3σ作为控制图控制界限的方法进行了改进,建立了确定最佳控制界限(Kσ)的数学模型与最优控制界限(K)的算式。通过实例对优化结果和现行“x±3σ”方法的结果进行了比较和分析,进一步说明了该方法的优越性。     

Turbo码Log-MAP译码算法简化实现的研究

Log-MAP算法实现Turbo译码时,要用查表等方法进行修正项的近似计算。用误差传播理论推导出Log-MAP算法大规模集成电路实现时状态度量和对数似然值等的精度要求,明确了量化方案,并由此得出计算修正项所需要的精度由信道接收值量化精度决定。理论上解释了信道接收值量化间隔为0.25时,8级查表就可以满足译码精度要求;也解释了高信噪比条件下,由于量化误差的传播,修正项可以忽略不计,此时Max-Log-MAP算法与Log-MAP算法一样,也是最优译码算法。根据推导出的对修正项精度的要求,结合修正项函数值分布特点,提出用6级非均匀查表计算修正项的方法。该方法能达到16级查表精度,在实现上比8级均匀查表简单。计算机仿真证明了上述结论。     

基于循环统计量的直升机齿轮箱轴承故障早期检测

在分析齿轮箱振动信号的基础上,提出了基于循环统计量的轴承故障早期检测方法,阐述了表征故障的一维和二维循环平稳特征。该方法利用信号与噪声具有不同循环频率的特性实现了信噪分离,能够比较容易地从复杂背景中提取出微弱的特征信息。最后在某型直升机齿轮箱轴承故障的早期检测中进行了实验验证。结果表明,该方法优于功率谱和解调分析,能够提取故障的早期特征。     

反求工程中经济型快速测量装置的研究

设计了结构简单经济实用的快速测量装置,采用分区域数据补偿方法进行误差补偿,提高了系统的测量精度,将有助于反求工程中测量效率的提高。     

Advanced optimization of gas turbine aero-engine transient performance using linkage-learning genetic algorithm: Part I,building blocks detection and optimization in runway

This paper proposes a Linkage Learning Genetic Algorithm (LLGA) based on the messy Genetic Algorithm (mGA) to optimize the Min-Max fuel controller performance in Gas Turbine Engine (GTE). For this purpose, a GTE fuel controller Simulink model based on the Min-Max selection strategy is firstly built. Then, the objective function that considers both performance indices (response time and fuel consumption) and penalty items (fluctuation, tracking error, overspeed and acceleration/deceleration) is established to quantify the controller performance. Next, the task to optimize the fuel controller is converted to find the optimization gains combination that could minimize the objective function while satisfying constraints and limitations. In order to reduce the optimization time and to avoid trapping in the local optimums, two kinds of building block detection methods including lower fitness value method and bigger fitness value change method are proposed to determine the most important bits which have more contribution on fitness value of the chromosomes. Then the procedures to apply LLGA in controller gains tuning are specified stepwise and the optimization results in runway condition are depicted subsequently. Finally, the comparison is made between the LLGA and the simple GA in GTE controller optimization to confirm the effectiveness of the proposed approach. The results show that the LLGA method can get better solution than simple GA within the same iterations or optimization time. The extension applications of the LLGA method in other flight conditions and the complete flight mission simulation will be carried out in part II.     

An enhanced least squares residual RAIM algorithm based on optimal decentralized factor

The Least Squares Residual (LSR) algorithm is commonly used in the Receiver Autonomous Integrity Monitoring (RAIM). However, LSR algorithm presents high Missed Detection Risk (MDR) caused by a large-slope faulty satellite and high False Alert Risk (FAR) caused by a small-slope faulty satellite. In this paper, the LSR algorithm is improved to reduce the MDR for a large-slope faulty satellite and the FAR for a small-slope faulty satellite. Based on the analysis of the vertical critical slope, the optimal decentralized factor is defined and the optimal test statistic is conceived, which can minimize the FAR with the premise that the MDR does not exceed its allowable value of all three directions. To construct a new test statistic approximating to the optimal test statistic, the Optimal Decentralized Factor weighted LSR (ODF-LSR) algorithm is proposed. The new test statistic maintains the sum of pseudo-range residual squares, but the specific pseudo-range residual is weighted with a parameter related to the optimal decentralized factor. The new test statistic has the same decentralized parameter with the optimal test statistic when single faulty satellite exists, and the difference between the expectation of the new test statistic and the optimal test statistic is the minimum when no faulty satellite exists. The performance of the ODF-LSR algorithm is demonstrated by simulation experiments.