基于SVM和广义粗糙度特征的航空发动机振动故障诊断方法

通过对航空发动机振动信号进行小波分解,依据多尺度空间局部能量分布和粗糙性提取基于子带信号能量加权广义粗糙度特征实现对振动情况的描述.然后将上述特征送入支持向量机(support vector machine,简称SVM)分类器进行训练,根据分类器的输出结果判断航空发动机的工作状态和故障类型.通过对实测航空发动机试车时得到的振动信号的实验分析结果表明,该算法可以有效地识别发动机的振动故障.      

关于一类非线性映射迭代序列收敛的等价性

本文在适当放宽不动点定理的条件下,分别证明了Mann迭代序列与Noor迭代序列收敛的等价性以及Mann迭代序列与Ishikawa迭代序列收敛的等价性。     

HISTORICAL PROCEDURES AND G-DSG METHOD BASED MANUFACTURING PLANNING

Oriented to CAD/CAM seamless integration, this paper presents an idea for synthetically considering the qualitative history model, which represents the whole course of modeling, and the quantitative geometry model, which contains the extended Brep model, CSG and feature pedigree. History model building captures in background the dynamic interactive definition of engineering requirement and then explicitly conveys the original intention to successive application layers, which isc onductive to the decision support of manufacturing planning in not only automatic geometry re-constructing but also machining set-up. G-DSG theory as an earlier achievement is applied to generate the topology-independent generalized mid-model as an input to manufacturing planning, which istherefore simplified and its accuracy is simultaneously improved. Manufacturing planning lays emphasis on optimizing the mapping in both geometry and function from part itself to detail machining scheme. Comparatively, process planning pays more attention to the mapping to those items like tool, fixture, etc. Theoretically, such an idea is also beneficial to realizing the parametric NC machining trajectory generation and maintaining its dynamic consistency with the update of the design model.     

多态故障树广义负前馈自动建树算法的研究及其应用

阐述了控制系统多态故障树自动建树的一种方法,提出了基于控制系统功能图的系统及其组成部件的规范化描述方法,提出了广义负前馈处理的算法,完善了自动建树中对复杂结构处理的算法;并结合一个飞控系统的实例,验证了算法的正确性。使得故障树自动建树朝着真正自动化的方向发展。     

Comprehensive outage compensation of real-time orbit and clock corrections with broadcast ephemeris for ambiguity-fixed precise point positioning

The main challenge in real-time precise point positioning (PPP) is that the data outages or large time lags in receiving precise orbit and clock corrections greatly degrade the continuity and real-time performance of PPP positioning. To solve this problem, instead of directly predicting orbit and clock corrections in previous researches, this paper presents an alternative approach of generating combined corrections including orbit error, satellite clock and receiver-related error with broadcast ephemeris. Using ambiguities and satellite fractional-cycle biases (FCBs) of previous epoch and the short-term predicted tropospheric delay through linear extrapolation model (LEM), combined corrections at current epoch are retrieved and weighted with multiple reference stations, and further broadcast to user for continuous enhanced positioning during outages of orbit and clock corrections. To validate the proposed method, two reference station network with different inter-station distance from National Geodetic Survey (NGS) network are used for experiments with six different time lags (i.e., 5 s, 10 s, 15 s, 30 s, 45 s and 60 s), and one set of data collected by unmanned aerial vehicle (UAV) is also used. The performance of LEM is investigated, and the troposphere prediction accuracy of low elevation (e.g., 10–20degrees) satellites has been improved by 44.1% to 79.0%. The average accuracy of combined corrections before and after LEM is used is improved by 12.5% to 77.3%. Without LEM, an accuracy of 2–3 cm can be maintained only in case of small time lags, while the accuracies with LEM are all better than 2 cm in case of different time lags. The performance of simulated kinematic PPP at user end is assessed in terms of positioning accuracy and epoch fix rate. In case of different time lags, after LEM is used, the average accuracy in horizontal direction is better than 3 cm, and the accuracy in up direction is better than 5 cm. At the same time, the epoch fix rate has also increased to varying degrees. The results of the UAV data show that in real kinematic environment, the proposed method can still maintain a positioning accuracy of several centimeters in case of 20 s time lag.     

基于改进GPC的无人直升机动态路径规划

针对小型无人直升机航迹受到风场扰动和导航系统定位误差影响下的航迹最优规划问题,建立了风扰动和导航误差影响下的飞行航迹线性模型。基于混合整数规划思想,采用粒子滤波改进广义模型预测控制算法实时规划航迹,降低了导航定位误差造成的航迹估计偏差,提高了航迹估计精度。仿真结果表明,该算法能够生成三维可行航迹并躲避障碍物,且规划时间和无人机能耗较传统方法显著减少。     

海杂波中广义符号恒虚警检测算法性能分析

分析了广义符号检测算法在仿真的高斯杂波背景和实测海杂波背景下,对2种目标（Sweding0型和Swerling II型）的检测性能,以及对实际渔船目标的检测性能。研究表明,随着脉冲数、参考单元数和信杂比的提高,该检测算法的检测性能有所提高;在低信杂比条件下,GS检测算法对SwedingII型目标的检测性能优于对Sweding0型目标的检测性能,在高信杂比的条件下,对Swerling 0型目标的检测性能优于对Swerling II型目标的检测性能。     

航空发动机持续适航安全风险评估方法研究

民航运输业正处在蓬勃发展阶段,保证飞行安全是民航的首要任务,飞机发动机作为飞机的心脏,其性能的好坏直接影响到飞行安全,采用合理的方法对发动机持续适航阶段的故障风险进行评估,对于提高飞行安全水平,保障航空运输业正常发展有着重要的作用。本文根据广义线性回归的相关理论,将广义线性回归模型引入发动机持续适航风险管理分析中,通过对发动机的故障风险水平进行实例评估验证,证明了该模型是一种准确的、有效的、可行的安全风险评价方法。     

基于广义马氏距离的混合型多属性决策的 TOPSIS方法

为了解决混合型多属性决策问题,将不同属性值转换为区间数形式。在基于马氏距离的逼近理想解排序法（TOPSIS）中,指标问线性强相关导致协方差矩阵为奇异矩阵,不能计算马氏距离。因此,定义了区间数的协方差矩阵,采用奇异值分解方法计算协方差矩阵的广义（M—P）逆矩阵。改进的算法克服了传统TOPSIS存在的指标信息重复、主观赋权不合理、隶属度难以确定,以及可能出现与理想解欧式距离近的方案与负理想解的欧式距离也近的不足。最后,给出了该方法的一个算例,结果表明该决策方法是实用和可行的。     

基于日最大风速记录的建筑群风环境评估方法

提出将各风向的风速比与日最大风速概率分布相结合,进行风环境评估,并按照风速大小划定建筑功能区域的基本方法。首先利用地面风速探头在风洞中对建筑群周边区域的风场进行定量测量,得出不同风向下各测点的风速比。再根据多年日最大风速记录和广义极值分布函数族,得出不同风向的日最大风速概率分布参数。由此即可求出各测点日最大风速超过风速阈值的概率。参照风环境评估准则,可对各区域的舒适度进行定量评估,并对其进行功能分区。通过对某高层建筑群的实验研究,验证了该方法的有效性和简便性,研究结果对建筑设计有直接的指导意义。