一种新的基于特征值融合的重力辅助导航适配区选择方法

重力匹配辅助导航定位系统中,有效地进行适配区选择可以得到更高精度的匹配定位结果,也可为航迹设计和航行规划提供参考。计算特征值是实现适配区选择的主要方法之一,目前的特征值方法主要有信息熵法、绝对粗糙度法、平均重力变化法（AGD）以及双近邻模式法等。通过仿真试验分析了各个特征值与对应的适配区及匹配定位效果的关系,结果表明这几种基于单个特征值的方法各有优缺点。因此,提出一种新的基于特征值融合的重力匹配适配区选择方法,综合已有特征值方法的优势,得到新的特征值计算方法。对比试验结果表明：相比现有单一的特征值方法,新方法和匹配定位结果有更好的相关性和对应性,可以更加准确有效地对重力适配区进行划分和选择。     

复杂装备研制项目的风险源识别

大型复杂装备研制项目高风险与参研单位多的特点使得研制过程中风险传导时有发生。针对风险传导要素风险源的识别问题,提出了一种基于关联规则(AR)与决策实验室分析法(DEMATEL)的风险源识别方法。该方法从数据挖掘的角度,先求解出风险类型与风险因素的关联规则,再求解出风险源之间的影响程度,最后通过DEMATEL得到各风险源相关参数。并且对某参研单位数据库中某阶段的数据用此方法完成了风险源的识别,识别结果显示了各风险类型对应的风险源以及易导致研制项目发生风险传导的风险源。     

An intelligent approach for flight risk prediction under icing conditions

Flight risk prediction is significant in improving the flight crew’s situational awareness because it allows them to adopt appropriate operation strategies to prevent risk expansion caused by abnormal conditions, especially aircraft icing conditions. The flight risk space representing the nonlinear mapping relations between risk degree and the three-dimensional commanded vector(commanded airspeed, commanded bank angle, and commanded vertical velocity) is developed to provide the crew with practi...     

Breakthrough detection in electrochemical discharge drilling to enhance machining stability

Film cooling holes are widely used in aero-engine turbine blades. These blades feature large numbers of holes with complex angles and require a high level of surface integrity. Electrochemical discharge drilling(ECDD) combines the high efficiency of electrical discharge drilling(EDD) with high quality of electrochemical drilling(ECD). However, due to the existence of a variety of energy for material removal, accurate and timely detection of breakthroughs is fraught with difficulties. An insuffic...     

A robust Poisson multi-Bernoulli filter for multi-target tracking based on arithmetic average fusion

The coalescence and missed detection are two key challenges in Multi-Target Tracking (MTT). To balance the tracking accuracy and real-time performance, the existing Random Finite Set (RFS) based filters are generally difficult to handle the above problems simultaneously, such as the Track-Oriented marginal Multi-Bernoulli/Poisson (TOMB/P) and Measurement-Oriented marginal Multi-Bernoulli/Poisson (MOMB/P) filters. Based on the Arithmetic Average (AA) fusion rule, this paper proposes a novel fusion framework for the Poisson Multi-Bernoulli (PMB) filter, which integrates both the advantages of the TOMB/P filter in dealing with missed detection and the advantages of the MOMB/P filter in dealing with coalescence. In order to fuse the different PMB distributions, the Bernoulli components in different Multi-Bernoulli (MB) distributions are associated with each other by Kullback-Leibler Divergence (KLD) minimization. Moreover, an adaptive AA fusion rule is designed on the basis of the exponential fusion weights, which utilizes the TOMB/P and MOMB/P updates to solve these difficulties in MTT. Finally, by comparing with the TOMB/P and MOMB/P filters, the performance of the proposed filter in terms of accuracy and efficiency is demonstrated in three challenging scenarios.