基于DSmT的航空发动机早期振动故障融合诊断方法

提出在航空发动机多个部位安装多个振动传感器组成传感器网络.采用多传感器信息融合技术进行早期振动故障的诊断方法,并引入Dezert-Smarandache理论(DSmT)来处理由早期微弱故障本身所导致的各个传感器信息相互冲突的问题.在构建的早期微弱故障诊断系统框架中,采用基于本征模态函数(IMF)的信息熵特征提取方法提取各路振动数据的特征,采用反向传播(BP)神经网络完成对故障属性的判断并生成各种故障模式的基本置信分配,最后根据DSmT融合规则得到最终的诊断结果.算例表明采用该方法可以有效地解决早期微弱故障条件下的高冲突信息融合问题,故障诊断结果准确可靠.      

基于改进D-S证据理论的航空发动机转子故障决策融合诊断研究

针对单一传感器的测量信息难以准确、全面地反映航空发动机转子、轴承和齿轮的工作状况,进而造成振动故障诊断难度大的问题,提出安装多个振动传感器组成传感器网络,建立基于多传感器信息的发动机转子故障决策融合诊断系统。由于多传感器系统不可避免地会存在各传感器信息不一致、信息冲突的情形,因此针对该融合诊断系统的信号测量、信息预处理、特征提取、故障诊断及决策融合5个环节,重点研究了决策融合环节的Dempster-Shafer（D-S）证据决策融合方法存在的冲突证据融合失效问题。通过分析原因,从避免“一票否决”现象和证据加权平均两个方面进行改进,提出了改进D-S证据融合方法,并应用于航空发动机转子的模拟故障决策融合诊断中。结果表明基于D-S证据理论对3个传感器的单一诊断结果进行决策融合,能得到比任一单个传感器更准确、可靠的结果;而改进D-S证据融合方法由于能在一定程度上克服冲突证据融合带来的失效问题,且能同时兼顾处理好非冲突证据的融合,故其对于证据冲突和非冲突情形都取得了较好的融合效果,因此总的分类正确率要高于常规D-S算法和PCR5算法。     

基于D-S证据理论的目标属性辨识研究

D—S证据组合理论已经成为不确定性推理的一种重要方法，基于该理论的多传感器决策层信息融合已得到广泛应用。本文在简要介绍D—S证据组合理论框架基础上，阐述了基于D—S证据组合理论的信息融合一般步骤及决策层判决方法；分析了发生证据严重冲突时，Dempster证据组合规则出现的不可靠和不合理的本质原因，介绍了针对D—S证据组合规则进行修正的几种主要方法；最后，提出了需要继续深入探讨的问题。     

于不确定性与重要度的改进DSmT健康状态评估

针对目前健康状态评估准确度不高、客观性不强的问题,引入评估指标的不确定性和重要度,提出一种基于不确定性和重要度的改进DSmT（Dezert Smarandache theory）健康状态评估方法.首先,引入指标不确定性和重要度作为加权因子,能够得到比较合理的指标权重;其次,采用模糊综合评判方法,通过构造三角形梯形隶属度函数确定各指标的广义基本信度赋值;然后,基于指标权重对广义基本信度赋值进行改进DSmT融合,得到各指标的广义基本信度赋值加权融合后的评估结果;最后,以某供电系统为例进行了实例验证,结果表明该方法能够赋予各评估指标较合理的权重,健康状态评估结果与系统实际运行状态相符.      

基于云模型和改进D-S证据理论的目标识别决策方法

在目标识别决策系统中,多探测器多源信息融合的模糊性和不确定性以及各探测周期所得信息的冲突互斥会造成目标识别决策不精准。为解决这一问题,提出基于云模型和改进D-S （Dempster-Shafer）证据理论的目标识别决策方法。首先,将目标识别准确性这一语言评价值划分为不同评价区间等级,以不同评价等级标准云为参照将各探测器各探测周期所得信息转化为云决策矩阵,得出各周期各等级隶属度,进而构建出基本概率分配函数（mass函数）;其次,基于证据理论引入冲突度、差异度、离散度3类衡量冲突大小的参数,定义了一种新的证据冲突参数,同时改进证据冲突融合算法,对各探测器各周期证据体进行修正并融合;再次,结合各探测器权重加权得出各目标综合识别决策的mass函数对目标进行决策;最后,结合算例,验证该方法的适用性,并与其他方法相对比验证了本文方法的优越性。     

证据冲突下自适应融合目标识别算法

 利用证据理论对空中目标识别系统的观测信息融合时,Dempster规则对低冲突信息的融合结果较为理想,但无法对高冲突信息有效融合。Dubois &; Prade(DP)规则及证据折扣法可对高冲突信息进行合理融合。为使不同融合方法发挥各自优势,提出一种自适应融合算法。首先将矛盾因子和证据距离两者结合以更全面地表示证据冲突程度,当冲突较小时,选用Dempster规则,反之,根据冲突的具体情况选择使用DP规则或证据折扣法。通过目标识别实验对多种算法进行了对比,表明本文算法既能对高冲突证据进行合理融合,又能使融合结果快速收敛,可以有效地提高识别速度及正确率。     

信息融合图像识别算法及其在三维飞机图像识别中的应用研究

将D S证据推理与不变矩理论相结合,提出了信息融合图像识别算法,并应用于三维飞机图像的识别。构造了基本置信指派函数,建立了分类规则,针对Dempster组合规则只适用于高置信度、低冲突性的情况,应用可解决证据冲突的加权分配冲突法及吸收法,完成了三维飞机图像识别的仿真,比较了3种组合规则的识别效果,结果表明吸收法识别率最高。     

多传感器协同探测证据理论分类融合方法

随着智能化、网络化集群作战等理念和技术的兴起,精确制导武器越来越向智能化、协同化方向发展。多传感器协同探测能够针对不同的探测任务背景和作战需求,提升目标探测性能,还可以跨域整合多种探测平台。但是由于信息的不确定性等特点,使得多传感器数据直接融合可能造成决策困难。因此,在证据理论体系下对信息融合的有效性进行合理分析与度量是很有必要的。提出了一种基于Deng熵的证据理论分类融合算法,以熵减为主要思想,将证据进行分类融合。在决策过程中,将含有证据数最多的类别融合结果作为总体融合结果,避免高冲突证据的影响,提升融合结果的信息有效性。采用算例说明了所提方法不仅能够得到合理正确的结果,并且融合可靠性较高,便于决策与后续的信息处理。     

证据推理冲突问题研究

证据推理是一种重要的人工智能方法,广泛应用于数据融合、数据挖掘和智能决策。但 Dempster组合规则对于高冲突情况的处理不是十分合理的。首先研究了几种组合规则的改进方法和造成其缺陷的机理,给出一类组合规则的改进方法,基于有无先验给出两类算法。仿真结果表明新的证据推理组合规则在处理冲突方面的性能得到了明显的改进。     

一种有效的基于DSmT的合成公式

针对DSmT在解决强冲突证据融合问题时存在的不足,提出了一种有效的冲突证据合成方法,即在保留冲突焦元的基础上对冲突量进行重新分配。仿真结果表明,新的合成公式提高了目标识别的可靠性与合理性,即使对于高度冲突的证据,也能够取得理想的合成结果。     

基于Faster-RCNN 的机场跑道异物识别定位技术研究

针对机场跑道异物(FOD) 识别检测，分析了机场跑道环境特性，建立了针对机场FOD图像识别数据库， 提出了一种基于Faster-RCNN 的机场跑道异物识别定位系统，通过无人机系统对机场跑道进行图像采集，运用 Faster-RCNN 算法框架完成异物种类识别，并结合无人机地理位置信息进行位置换算求解，得到机场FOD 的 类别信息和位置信息。经验证，该系统可高效完成机场FOD 检测识别及定位任务。     

A multi-aircraft conflict detection and resolution method for 4-dimensional trajectory-based operation

Conflict Detection and Resolution(CDR) is the key to ensure aviation safety based on Trajectory Prediction(TP). Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional(4D) Trajectory-Based Operation(4DTBO), which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CDR from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CDR scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism(STP) for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.     

An information-volume-based distance measure for decision-making

D-S evidence theory, as a general framework for reasoning with uncertainty, allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy measure. However, the mass assignments given by unknown information sources are disordered. How to measure the difference between the mass assignments has aroused people’s interest. In this paper, inspired by the information volume, a novel distance-based measure is proposed to measure the difference between mass assignments. The method can refine the uncertain information given by experts and compare the refined information to obtain the difference between mass assignments. At the same time, it is verified that the measure not only meets the properties of distance, but also proves the superiority of the proposed Information Volume Distance (IVD) through simulation experiments. Meanwhile, in the process of information fusion, the reliability of each source could be quantified through IVD. Therefore, based on IVD, a new multi-source information algorithm is proposed to solve the problem of multi-source information fusion. Moreover, algorithm is applied to decision-making problem and compare with other methods to verify the effectiveness.     

An improved α-cut approach to transforming fuzzy membership function into basic belief assignment

In practical applications, pieces of evidence originated from different sources might be modeled by different uncertainty theories. To implement the evidence combination under the Dempster–Shafer evidence theory(DST) framework, transformations from the other type of uncertainty representation into the basic belief assignment are needed. a-Cut is an important approach to transforming a fuzzy membership function into a basic belief assignment, which provides a bridge between the fuzzy set theory and the DST. Some drawbacks of the traditional a-cut approach caused by its normalization step are pointed out in this paper. An improved a-cut approach is proposed, which can counteract the drawbacks of the traditional a-cut approach and has good properties. Illustrative examples, experiments and related analyses are provided to show the rationality of the improved a-cut approach.     

Principles of Invariance in Radiative Transfer

We have reviewed the principle of invariance, its applications and its usefulness for obtaining the radiation field in semi-infinite and finite atmospheres. Various laws of scattering in dispersive media and the consequent radiation field are studied. The H-functions and X- and Y-functions in semi-infinite and finite media respectively are derived in a few cases. The Discrete Space Theory (DST) which is a general form of the Principle of Invariance is described. The method of addition of layers with general properties, is shown to describe all the properties of multiple scattering. A few examples of the application of DST such as polarization, line formation in expanding stellar atmospheres, etc., and a numerical analysis of DST are presented. Other developments in the theory of radiative transfer are briefly described. This revised version was published online in June 2006 with corrections to the Cover Date.     

外物损伤对风扇／压气机叶片高循环疲劳性能影响的研究

对外物损伤(FOD)对航空发动机风扇/压气机叶片高循环疲劳(HCF)性能影响的国内外研究进行了综述和分析,介绍了美、英等国通过实施涡轮发动机HCF研究计划在FOD对叶片HCF性能的影响研究方面所取得的进展和成果,总结了中国近年来对FOD问题的研究内容,指出了中国该项技术研究的不足和差距,并对需要进一步深入研究的关键技术问题提出了建议。     

A clustering based method to complete frame of discernment

When the existing information does not contain all categories, the Generalized Evidence Theory (GET) can deal with information fusion. However, the question of how to determine the number of categories through GET is still intriguing. To address this question, a modified k-means clustering, named centers initialized clustering is proposed, filling the gap of identification and complement of the frame of discernment. Based on this clustering method, the number of categories is determined. The initialized centers selected by center density keep the cluster results constant, enhancing the stability of clustering results. Besides, constructing Generalized basic Probability Assignment (GBPA) modules in a conservative way improves the reliability of the results. The mass of empty set in combined GBPAs is the indicator of the number of categories. Experiments on real and artificial data sets are conducted to show the effectiveness.     

De-combination of belief function based on optimization

In the theory of belief functions, the evidence combination is a kind of decision-level information fusion. Given two or more Basic Belief Assignments(BBAs) originated from different information sources, the combination rule is used to combine them to expect a better decision result. When only a combined BBA is given and original BBAs are discarded, if one wants to analyze the difference between the information sources, evidence de-combination is needed to determine the original BBAs. Evidence d...     

叶片外物损伤容限设计的本质特点及设计准则的发展

通过对风扇/压气机叶片外物损伤及其失效特点的深入分析,认为叶片外物损伤容限设计的本质是考虑外物损伤影响的叶片振动应力设计.通过对国内外发动机设计规范和标准的分析和回顾,将外物损伤容限设计准则的发展分为3个阶段:①50年代初-60年代末,以外物损伤(FOD)的预防和维护为主;②70年代初-90年代末,等效为应力集中系数K_t≤3的缺口容限设计;③2000年以来,FOD的概率容限设计.最后对我国外物损伤容限设计的研究方向提出了建议.      

Experimental research of active vibration and noise control of electrically controlled rotor

Electrically Controlled Rotor (ECR), also called as swashplateless rotor, applies blade pitch inputs via trailing-edge flaps system instead of traditional swashplate mechanism. In addition to primary control, rotor vibration reduction and noise alleviation are also achievable via applying higher harmonic control inputs with the trailing-edge flaps. In this paper, the feasibility of ECR to reduce vibration and noise actively is verified experimentally. Firstly, the test scheme of ECR active vibration and noise control is proposed, and the ECR test platform is modified according to the test scheme. Then, an adaptive control algorithm based on Kalman filter is developed. Lastly, hover and wind tunnel tests is performed to verify the feasibility of ECR active vibration and noise control. The results demonstrate that the ECR are effective for reducing rotor vibration and noise simultaneously. In the hover condition, the ECR can reduce the in-plane hub vibration by 42% and the in-plane noise by 4 dB. In wind tunnel condition, ECR can reduce the hub vibration by 75% and the BVI noise by 3 dB.