基于光谱信息散度的光谱解混算法

光谱解混是高光谱遥感定量化的关键,提出了一种基于光谱信息散度和光谱混合分析的光谱解混改进算法(SID-SMA,Spectral Information Divergence-Spectral Mixed Analysis).以光谱信息散度判定最优端元子集,端元选择时采用端元的初选和二次选择来提高端元选择的精度,得到较小的丰度估计误差.通过光谱库模拟数据的结果可以看出,SID-SMA的端元选择精度和丰度估计精度要优于其他算法,当信噪比为100∶ 1时,算法端元选择正确率达到了99.8%,29个端元的丰度估计总误差小于0.1,并且算法的速度较快.     

产品开发早期基于核心工艺框架的工艺设计

关于早期工艺设计理论方法的研究都是以特征信息为基础,不能利用早期阶段粗粒 度、非完备的产品信息.为此,采用关键特性表示粗粒度、非完备的产品信息,提出基于核 心工艺框架的工艺设计方法.核心工艺框架是对满足关键特性要求的工艺计划的抽象,可表 达产品族或零件族中各种变型的核心工艺内容,根据分支和存在规则快速配置工艺计划.基 于核心工艺框架的工艺设计过程包括4个步骤:确定产品族/零件族,检索核心工艺框架, 配置核心工艺和工艺路线设计,有效性规则、原理性规则和定制性规则确保工艺设计的准确 性.最后通过有翼导弹的弹翼主梁的加工工艺验证了此方法的可行性.      

Satellite selection methods for multi-constellation advanced RAIM

The increased number of potential threat modes under multi-constellation advanced receiver autonomy integrity monitoring (ARAIM) requires an increase in the number of subsets and a correspondingly high computational load. A new satellite selection method based on integrity support message (ISM) parameters is proposed and compared with GDOP-based selection. The performance was tested on five days of data measurements from 21 multi-global navigation satellite system experiment (MGEX) stations distributed around the world, as well as simulation using the broadcast ephemeris. The results show that the proposed ISM-based satellite selection method is highly compatible with the baseline ARAIM. This method could reduce the computational times by about 60–70% quickly, with minimising vertical protection level (VPL) loss, which was consistently within 1 m, even a reduced VPL value in some epochs, and resulting in an improved availability. The simulation results were similar to the MGEX data. It appears that the application of ISM-based satellite selection can effectively reduce computational burden with a minimal impact on availability.     

关于加工中心选型订货的几个问题

阐述了选型、订货加工中心的基础知识，订货原则，选型订货方法及工作步骤。     

一种新的导航星选取算法研究

在导航星表的建立过程中，由于恒星的数量太多，往往要进行筛选，通常这种选择复杂费时，而结果往往并不是最优的。本文引入了动态星等阈值分布函数，将传统星等阈值过滤算法中的静态阈值用动态星等阈值代替，建立了一种新的动态星等阈值过滤选择模式。而基于统计学习理论的支持向量机方法为求解高维非线性动态星等阈值分布函数提供了新的途径。本文讨论了这种基于支持向量机的导航星自动选择算法——回归选取算法。实验表明，用该算法所选取的导航星表，导航星数量少、分布均匀性好。同时它还能适应多种任务的导航星选取要求，具有很强的通用性。     

挠性杆的镗加工技术

针对挠性杆的结构特点和加工难点,提出了有效的工艺措施,从装夹定位、刀具材料与几何参数选择、刃磨方法、切削用量的选择,以及挠性杆内应力的分析等方面详细地阐述了加工过程中的关键技术,解决了挠性杆镗削加工的技术难题。     

一种载人航天概率风险评价数据选用与分析方法

概率风险评价(PRA)方法是一项成熟的量化风险评估技术,而可靠性相关数据不足,制约着该方法在国内载人航天领域的应用。针对这一问题,结合NASA的PRA工作经验,提出了一种适合国内载人航天PRA数据选用与分析的方法,综合运用产品的通用数据与特定数据,采用贝叶斯等数据融合方法,对产品进行量化评价。通过航天典型产品案例,与经典评估方法进行对比分析,结果表明,此方法更能反映产品的失效特性。文章提出的方法,可用于载人航天等具有小子样特征的产品PRA数据的选用与分析,为我国载人航天开展PRA工作提供参考。     

A multi-criteria fusion feature selection algorithm for fault diagnosis of helicopter planetary gear train

Planetary gear train is a prominent component of helicopter transmission system and its health is of great significance for the flight safety of the helicopter. During health condition monitoring, the selection of a fault sensitive feature subset is meaningful for fault diagnosis of helicopter planetary gear train. According to actual situation, this paper proposed a multi-criteria fusion feature selection algorithm (MCFFSA) to identify an optimal feature subset from the high-dimensional original feature space. In MCFFSA, a fault feature set of multiple domains, including time domain, frequency domain and wavelet domain, is first extracted from the raw vibration dataset. Four targeted criteria are then fused by multi-objective evolutionary algorithm based on decomposition (MOEA/D) to find Proto-efficient subsets, wherein two criteria for measuring diagnostic performance are assessed by sparse Bayesian extreme learning machine (SBELM). Further, F-measure is adopted to identify the optimal feature subset, which was employed for subsequent fault diagnosis. The effectiveness of MCFFSA is validated through six fault recognition datasets from a real helicopter transmission platform. The experimental results illustrate the superiority of combination of MOEA/D and SBELM in MCFFSA, and comparative analysis demonstrates that the optimal feature subset provided by MCFFSA can achieve a better diagnosis performance than other algorithms.     

基于知识重用的刀具选配技术研究

在分析了传统刀具选配模式存在的不足的基础上,对基于知识重用的刀具选择技术进行了研究.采用实例推理技术进行刀具智能选择,对刀具智能选择过程中涉及的特征提取、知识表示、检索策略、相似度计算等实例推理的关键技术进行了研究.