基于贝叶斯方法与稳健理论的滚动轴承摩擦力矩不确定度建立方法

基于贝叶斯方法与稳健化理论,提出一种未知分布时间序列不确定度的建立方法。该方法以中位数估计与Huber M估计融合方法分析时间序列数据的稳健性,构建贝叶斯先验分布,并与实验数据建立贝叶斯后验分布,创建以贝叶斯后验分布建立时间序列数据的不确定度。在显著性水平为0～0.1,通过对滚动轴承摩擦力矩分析,中位数估计与Huber M估计相融合方法确定了滚动轴承摩擦力矩稳健数据的边界值、显著性水平,构建了贝叶斯先验分布。以贝叶斯后验分布构建滚动轴承摩擦力矩不确定度。与经典统计学得到的不确定度比较,在相同置信水平下,该方法缩短了评估区间,提高了评估精度0～50%。该融合方法以稳健数据构建先验分布,提供一种贝叶斯方法先验分布建立方法;采用中位数估计与Huber M估计融合方法确定了数据显著性水平和边界值的确定,减小置信水平与稳健数据边界值主观确定的误差;为未知分布时间序列的不确定度建立提供了一种理论。     

加速退化试验测量不确定度评定方法

受测量分散性、仪器误差等因素影响，加速退化试验中存在测量不确定性问题。提出了加速退化试验测量不确定度的传播与评定方法，以提高试验评估结果的准确性和可信性。首先，介绍了加速退化试验中的测量不确定度来源，并结合维纳过程加速退化模型参数估计过程分析了测量不确定度的传播效应；其次，分别利用测量不确定度指南评定法（GUM）和蒙特卡洛法，量化评定了加速退化试验中性能观测数据测量不确定度对正常应力水平下产品可靠性评估结果的影响；最后，采用某型空间用高分子传感器案例对本文所提方法进行验证，并针对2种方法的估计结果进行了对比分析，验证了所提出方法的有效性。     

最小二乘独立线性度的测量不确定度

介绍了用最小二乘法评价线性测量系统线性度指标时，测量结果的不确定分析和评价过程，讨论了影响评价结果不确定度的几个主要误差来源，给出了减小线性度指标评价不确定度的主要措施：（1）环境控制措施，以减少环境带来的不确定度；（2）选取高精度信号，以减少信号源带来的不确定度。通过实例，给出了线性度指标不确定度分析和评价结果。本文方法及结论可应在于讲理标准进行性度指标的不确定分析上，也可用于估计线性度指标本身的不确定度。     

角速度波动率测量的数据处理和不确定度分析

本文在对角速度波动率测量技术研究的基础上，提出了一些自己的看法，并对一些相关术语进行了定义，同时，对角速度波动率测量方法的不确定度评定进行了分析。最后，通过数据处理软件对实验数据进行了分析和验证。     

温度传感器辐射修正校准的准确牲研究

为了确定温度传感器辐射修正校准的准确性，需要对温度传感器辐射修正校准结果进行对比及不确定度分析。本文介绍了在热校准风洞中进行温度传感器辐射修正校准的结果，并做了对比研究和不确定度分析。     

飞行器气动参数估计不确定度评价方法研究

为了有效地利用飞行器气动参数估计结果,必须同时给出估计结果的不确定度,因此研究了不确定度评价方法.当试验样本较多时,样本标准差具有明确的统计含义,比分散度能够更好地描述参数估计的不确定度.对于单个试验样本,基于不确定度椭球导出的C-R(Cramer-Rao)界是参数估计不确定度最好的理论预测,但利用飞行实测数据得到的C-R界普遍比样本标准差小.鉴于此,通过在低频有色噪声的基础上构造白噪声的方法,得到了一种C-R界修正方法,并通过仿真算例验证了修正方法的正确性.最后,将C-R界修正方法应用于飞行实测数据,得到的修正C-R界与利用多次飞行试验参数估计结果计算的样本标准差比较一致,表明该修正方法能够较好地给出参数估计的不确定度区间.     

基于贝叶斯框架的旋翼气动力数据融合

由于气动环境的复杂性,旋翼在气动评估中存在较多不确定性且对旋翼性能影响较大。当前旋翼气动评估方法不能考虑气动数据不确定性,本文将数据融合技术应用于旋翼气动预测以在记及某些不确定因素影响的条件下,获得具有更高可信度的气动力分布及置信区间,为进一步开展旋翼气动数据的不确定度分析及工程应用奠定基础。基于不同来源的气动力数据均为正态分布的独立随机变量这一假设,将分布气动数据和测量值之间的关系作为融合准则,以实现最佳匹配测量值为目标,采用贝叶斯估计求解融合数据的最大后验概率分布,从而构建一种基于贝叶斯框架的气动数据融合方法。以UH-60A旋翼及Caradonna-Tung旋翼为例,采用所提方法进行不同来源气动数据的融合,对融合结果的估计方差与预测误差进行对比分析。结果表明,首先,所提方法对于输入数据的来源无特殊要求,能够给出融合结果的置信区间并降低不同来源数据的估计方差,基于此结果后续可进行不确定度分析与研究;其次,融合所得结果并不局限于不同来源数据之间,扩大了数据覆盖范围;最后,融合所得结果相比于单一数据来源更符合物理规律。     

三座主力低速风洞五台天平的精细化校准与不确定度的科学标定

本报告完成了三座主力低速风洞五台天平的精细化校准和不确定度的科学标定。采用本文方法算出的天平校准不确定度和风洞实验不确定度能够大幅度降低。     

压力传感器最小二乘直线不确定度评定及应用

主要介绍压力传感器最小二乘直线不确定度的评定方法,并结合试验数据,对测量结果不确定度和最小二乘直线不确定度进行了比较及说明。     

风洞数据不确定度分析方法

本文简要介绍了风洞数据不确定度分析方法。利用该方法不仅可以迅速地估算出试验数据的不确定度,为用户提供安全设计依据,而且还可以为风洞人员提供有效的试验质量监控方法。该方法已在一些国家推行,并正在形成标准。     

Detection and diagnosis of sensor and actuator failures using IMMestimator

An approach to detection and diagnosis of multiple failures in a dynamic system is proposed. It is based on the interacting multiple-model (IMM) estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural as well as parametric changes. The proposed approach provides an integrated framework for fault detection, diagnosis, and state estimation. It is able to detect and isolate multiple faults substantially more quickly and more reliably than many existing approaches. Its superiority is illustrated in two aircraft examples for single and double faults of both sensors and actuators, in the forms of “total”, “partial”, and simultaneous failures. Both deterministic and random fault scenarios are designed and used for testing and comparing the performance fairly. Some new performance indices are presented. The robustness of the proposed approach to the design of model transition probabilities, fault modeling errors, and the uncertainties of noise statistics are also evaluated     

Bernoulli particle flter with observer altitude for maritime radiation source tracking in the presence of measurement uncertainty

For maritime radiation source target tracking in particular electronic counter measures（ECM）environment,there exists two main problems which can deteriorate the tracking performance of traditional approaches.The frst problem is the poor observability of the radiation source.The second one is the measurement uncertainty which includes the uncertainty of the target appearing/disappearing and the detection uncertainty（false and missed detections）.A novel approach is proposed in this paper for tracking maritime radiation source in the presence of measurement uncertainty.To solve the poor observability of maritime radiation source target,using the radiation source motion restriction,the observer altitude information is incorporated into the bearings-only tracking（BOT）method to obtain the unique target localization.Then the two uncertainties in the ECM environment are modeled by the random fnite set（RFS）theory and the Bernoulli fltering method with the observer altitude is adopted to solve the tracking problem of maritime radiation source in such context.Simulation experiments verify the validity of the proposed approach for tracking maritime radiation source,and also demonstrate the superiority of the method compared with the traditional integrated probabilistic data association（IPDA）method.The tracking performance under different conditions,particularly those involving different duration of radiation source opening and switching-off,indicates that the method to solve our problem is robust and effective.     

OTHR multipath tracking with uncertain coordinate registration

Multipath probabilistic data association (MPDA) exploits discrete multipath propagation to improve tracking performance for systems such as over-the-horizon radar (OTHR). The original formulation assumed a known ionospheric environment for mapping radar measurements to ground coordinates. We consider an extension of the technique that allows for ionospheric uncertainties affecting the transformation between slant and ground coordinates in addition to the usual sensor noise. A new technique, MPDA for uncertain coordinate registration (MPCR), is described and tested on simulated and real OTHR data. The study assumes a two-layer spherical mirror ionosphere with random fluctuations of the ionospheric heights around known mean values. An extensive Monte Carlo analysis of track errors and track loss is carried out for MPCR under two scenarios and the results are compared with a baseline probabilistic data association (PDA) approach and with MPDA. The results indicate the high reliability of the MPCR approach.     

基于非概率模型的结构稳健可靠性设计方法

 基于非概率可靠性理论,将稳健设计和稳健可靠性的思想和方法用于结构设计,提出了结构的稳健可靠性设计方法。把结构设计归结为满足可靠性要求的多目标优化。其中,以非概率可靠性指标为约束,以极小化结构重量 (或造价)和极大化对不确定因素的稳健性为目标。目的在于使结构在满足可靠性要求的前提下,其重量 (或造价)和对不确定因素的稳健性达到协调最优。在不确定参量的已知数据很少的情况下,本方法为结构的可靠性设计提供了一种可能的选择。数值算例说明了文中方法的应用。     

A strategic flight conflict avoidance approach based on a memetic algorithm

Conflict avoidance （CA） plays a crucial role in guaranteeing the airspace safety. The cur- rent approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjust- ment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm （MA）, which can markedly improve search capability via a combination of population-based global search and local improve- ments made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm （GA） is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outper- formed the existing approaches including the GA .based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.     

考虑不确定性的复合材料加筋壁板后屈曲分析模型验证方法

复合材料加筋壁板在结构轻量化设计中，由于材料组分、几何尺寸具有不确定性，导致了壁板结构在服役条件下承载特性的不确定性。针对上述问题，提出了一种考虑参数不确定性的复合材料加筋壁板后屈曲模型验证方法。首先基于正交试验设计方法进行了不确定性参数的显著性分析，然后采用Kriging模型构建了能够表征后屈曲特性的代理模型，利用蒙特卡洛随机模拟获得加筋壁板后屈曲载荷概率分布，最后通过壁板结构在典型承载条件下的力学实验数据验证了分析模型的准确性。该分析方法对于壁板件在实际工程中的应用具有一定指导意义。     

飞机典型结构细节——紧固孔随机裂纹扩展分析

根据7475T761铝合金犬骨型试样在随机谱载荷作用下的试验结果,采用两种随机裂纹扩展分析的方法,即通用的和解析的分析方法,研究了飞机典型结构细节——紧固孔中疲劳裂纹扩展的概率累积损伤,给出了概率裂纹扩展轨迹、裂纹扩展损伤累积分布及裂纹超出数的概率。试验结果与预测结果的比较表明,两者十分吻合,能满足工程精度的要求,为飞机结构的耐久性和损伤容限评估提供了适用的分析手段。     

一种混合的扩展目标跟踪方法

与传统的目标跟踪不同,扩展目标跟踪（EOT）不忽略目标的轮廓特征,同时对目标的质心运动学状态和轮廓特征进行估计。基于随机矩阵的扩展目标跟踪方法用随机正定矩阵来描述目标的轮廓特征,并且建立了适合扩展目标跟踪的量测模型。为了改善目标机动时的跟踪性能,根据椭圆（体）与正定矩阵的关系,提出基于椭圆（体）拟合的扩展目标跟踪方法。进一步地,为了综合上述两类方法的优点,提出一种混合的扩展目标跟踪方法,能够根据目标机动与否在两类方法中进行选择。仿真结果表明,该混合方法的轮廓特征估计误差低于前述两类方法,质心运动学状态的估计性能也更好。     

Geometrical entropy approach for variable structure multiple-model estimation

The variable structure multiple-model(VSMM) estimation approach, one of the multiple-model(MM) estimation approaches, is popular in handling state estimation problems with mode uncertainties.In the VSMM algorithms, the model sequence set adaptation(MSA) plays a key role.The MSA methods are challenged in both theory and practice for the target modes and the real observation error distributions are usually uncertain in practice.In this paper, a geometrical entropy(GE) measure is proposed so that the MSA is achieved on the minimum geometrical entropy(MGE) principle.Consequently, the minimum geometrical entropy multiple-model(MGEMM) framework is proposed, and two suboptimal algorithms, the particle filter k-means minimum geometrical entropy multiple-model algorithm(PF-KMGEMM) as well as the particle filter adaptive minimum geometrical entropy multiple-model algorithm(PF-AMGEMM), are established for practical applications.The proposed algorithms are tested in three groups of maneuvering target tracking scenarios with mode and observation error distribution uncertainties.Numerical simulations have demonstrated that compared to several existing algorithms, the MGE-based algorithms can achieve more robust and accurate estimation results when the real observation error is inconsistent with a priori.     

基于径向基神经网络干扰观测器的空天飞行器自适应轨迹线性化控制

 研究了一种自适应轨迹线性化控制策略并应用于空天飞行器(ASV)飞行控制系统设计。通过理论分析指明当前轨迹线性化控制方法(TLC)对系统中的不确定存在鲁棒性不足的问题。为了解决这一问题,首先研究了一种径向基神经网络干扰观测器(RDO)技术,严格证明了RDO对于系统中不确定因素具有良好的逼近能力。然后利用RDO输出得到一种新的基于RDO的自适应TLC控制策略。神经网络自适应律采用Lyapunov方法设计,保证了闭环系统所有信号有界。最后采用新方案实现了ASV飞控系统,仿真结果表明整个闭环系统在鲁棒性能方面得到很大提高。