Multi-sensor optimal data fusion for INS/GPS/SAR integrated navigation system

INS/GPS/SAR integrated navigation system represents the trend of next generation navigation systems with the high performance of independence, high precision and reliability. This paper presents a new multi-sensor data fusion methodology for INS/GPS/SAR integrated navigation systems. This methodology combines local decentralized fusion with global optimal fusion to enhance the accuracy and reliability of integrated navigation systems. A decentralized estimation fusion method is established for individual integrations of GPS and SAR into INS to obtain the local optimal state estimations in a parallel manner. A global optimal estimation fusion theory is studied to fuse the local optimal estimations for generating the global optimal state estimation of INS/GPS/SAR integrated navigation systems. The global data fusion features a method of variance upper finiteness and a method of variance upper bound to ensure that the global optimal state estimation can be achieved under a general condition. Experimental results demonstrate that INS/GPS/SAR integrated navigation systems achieved by using the proposed methodology have a better performance than INS/GPS integrated systems.     

基于矢量化检测联邦滤波的INS/BDS/地磁组合导航容错方法

组合导航能够将多种类型的导航信息进行结合,实现优势互补,因此成为了目前导航应用领域的主要发展方向。然而,导航信息的增多势必会引入更多的风险源,从而降低导航系统的可靠性。基于联邦滤波的容错方法是目前抑制故障信息影响的主要解决手段,但是现有的故障容错方法普遍采用统一的检测机制,没有根据各个导航子系统的误差传播特性针对性地构建故障检测模型,因此会引起较高的误警率与漏检率。针对上述问题,提出了基于矢量化检测联邦滤波的INS/BDS/地磁组合导航容错方法。通过构建面向INS/BDS/地磁不同导航信息的故障检测函数,能够实现更加准确的矢量化信息分配,从而可以有效避免可用导航信息的损失以及故障导航信息对整体系统的影响。仿真结果表明,提出的方法可以有效隔离不同类型的故障信息,并减小其对无故障导航信息及整体系统的影响,从而提高了组合导航的精度和可靠性。     

基于序贯回归的小样本测试性验证试验方案

针对现有测试性验证试验方案难以实现较小样本量下满足置信水平要求的测试性评估问题,提出了基于序贯回归的小样本测试性验证试验方案。提出并证明了成败型试验序贯样本回归可行性假设;对序贯样本进行回归分析,实现了小样本下的测试性评估;建立了评估优化方案,实现了满足置信水平要求的测试性评估。实例验证表明:该方法可同时适用于有双方风险要求和置信水平要求的场合,且完所需样本量明显减少,在案例中平均减少了22.3%,最大减少了85%。      

Training effectiveness evaluation of helicopter emergency relief based on virtual simulation

Helicopters are playing an increasingly important part in emergency relief, such as earthquake rescue, firefighting and medical transport. With the development of virtual simulation technology, virtual simulation-based training is widely used in the training of the helicopter crew especially for the dangerous and costly missions mentioned above. A complete training effectiveness evaluation method is proposed to evaluate the trainees’ training effect based on virtual simulation in this paper. A key to this method is regarding the complicated process as a discrete event-activity flow system and establishing the evaluation indicator system. Then expert group and Analytical Network Process (ANP) are applied to determine the weight of indicators. When the training data are processed, there is a novel attempt to apply Fuzzy Comprehensive Evaluation (FCE) model to calculate the two categories of indicators. Eventually, an experiment and the analysis were carried out to validate the evaluation method.     

Real-time fault detection method based on belief rule base for aircraft navigation system

Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults. On account of this reason, we propose an online detection solution based on non-analytical model. In this article, the navigation system fault detection model is established based on belief rule base (BRB), where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output. To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update, a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization (EM) algorithm. Furthermore, the proposed method is verified by navigation experiment. Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model. The output of the detection model can track the fault state very well, and the faults can be diagnosed in real time and accurately. In addition, the detection ability, especially in the probability of false detection, is superior to offline optimization method, and thus the system reliability has great improvement.     

基于虚拟载荷校准试验的襟翼曲柄测载方法

飞行载荷测量是验证飞机结构完整性,完成飞机定型必需的试验项目。基于应变法的飞行载荷测量方法通过地面校准试验构建应变与加载载荷之间的对应关系,然后将飞行实测应变代入载荷模型求得飞行载荷。某型飞机襟翼驱动曲柄几何外形不规则,具有轴向弯折、截面非对称等特点,载荷测量存在困难。基于该襟翼驱动曲柄的运动机理及襟翼操纵机构的传力路径研究,对曲柄进行受力分析,提出曲柄载荷测量方法,并利用虚拟载荷校准试验的手段对本方法进行验证。结果表明,本文方法是正确、有效的。     

基于测试数据的卡箍非线性等效建模方法

为了快速准确地计算卡箍管路系统的振动响应,提出了基于测试数据的卡箍非线性等效建模方法。对卡箍直管系统进行低幅值激励的模态测试,利用试验数据对有限元模型进行修正,识别卡箍线性刚度、线性阻尼参数。对卡箍直管系统开展不同激励水平下的恒力测试,通过样条插值多项式法将恒力频响函数转换为恒位移、恒速度频响函数,并进一步识别卡箍非线性等效刚度、非线性等效阻尼,建立了考虑卡箍非线性的等效动力学模型。研究表明:该卡箍等效动力学模型的预测频响函数与试验频响函数的最大误差仅为-6.9%,可以有效地反映卡箍实际的刚度、阻尼特性,对解决卡箍管路系统的振动响应分析具有重要的指导意义。      

一种基于二次分配的测试性指标分配方法

针对现有主流测试性分配方法均为一次性分配,缺乏必要的反馈和修正,一旦有单元分配指标过高无法实现,会导致系统指标也无法实现的问题,提出了一种基于二次分配的测试性指标分配方法。利用基于反正切函数的改进故障率分配法实施初次分配,由单元开展测试性初步设计和预计,基于单元测试性指标预计结果判断是否需要实施再次分配,如需要再次分配,则基于单元相对难度系数的修正函数,对指标偏高/偏低的单元实施再次分配,得到最终分配结果。通过仿真算例和实例验证了二次分配方法的有效性和先进性。     

A novel optimal data fusion algorithm and its application for the integrated navigation system of missile

For Inertial Navigation System(INS)/Celestial Navigation System(CNS)/Global Navigation Satellite System(GNSS) integrated navigation system of the missile, the performance of data fusion algorithms based on the Cubature Kalman Filter(CKF) is seriously degraded when there are non-Gaussian noise and process-modeling errors in the system model. Therefore, a novel method is proposed, which is called Optimal Data Fusion algorithm based on the Adaptive Fading maximum Correntropy generalized high-degree...     

测试性研制阶段数据评估验证方法

分析了现有测试性验证方法应用情况,阐述了测试性研制阶段数据评估验证方法的必要性。通过与现有测试性验证方法的对比分析,提出了一种新的测试性验证方法,并说明了该验证方法的含义和特点。该验证方法可用于故障检测率、故障隔离率和虚警率的验证。建立了该验证方法的工作框架,包括验证要求、验证程序、验证技术和验证组织。重点阐述了该验证方法的两种工作方式实施流程、适用的最小样本量范围、测试性数据收集表格和测试性数据判据。其中,测试性数据收集表格可以记录故障检测、故障隔离和虚警信息。进行了案例应用,给出了数据分析结果和经验总结。案例应用表明该方法能够达到测试性验证的效果。     

涡轮泵试车数据单类支持向量机检测算法

为了在缺乏故障样本的情况下检测某型液体火箭发动机涡轮泵故障,实现基于不完整信息的状态决策,建立了基于v-支持向量分类器的单类支持向量机新异类检测模型。在分析了模型决策边界、支持向量和约束条件之间关系的基础上,为单类支持向量机引入并改进了序贯最小优化算法,提高了训练效率,解决了大样本训练问题。通过对某型液体火箭发动机涡轮泵历史试车数据的分析,结果表明,所建模型的训练速度得到了很大提高,对涡轮泵状态的检测效果良好。     

基于分布式仿真的导引头试验与评估技术研究

分析了未来导引头试验与评估的需求,提出了一种基于分布式仿真的导引头试验与评估系统的结构,分析了其关键技术。     

基于飞行试验数据的进气道畸变预测与试验验证

采用响应曲面的试验设计方法,构建了基于试飞数据的进气道压力畸变预测模型,进行不同飞行工况进气道畸变模型预测与飞行试验验证研究。研究结果表明:模型预测与飞行试验结果相比,综合压力畸变指数平均相对误差为421%,稳态周向畸变指数平均相对误差为799%,结果吻合良好,能够满足对该型进气道畸变预测要求;大迎角、侧滑及其组合飞行时,进气道内部附面层气流分离是造成进气道出口畸变的主要因素;进气道出口低压区的位置与飞行姿态角相对应,并在周向上向压气机的旋转方向有小范围偏转,偏转角度与发动机状态相关;采用“模型预测+飞行试验”的模式能够完整、安全高效地考核评估飞机进气道的畸变特性,具有很好的工程适用性。     

基于不确定性测度与支持度的测试性验前信息融合方法

针对目前验前信息融合方法存在主观性和单一性的缺陷,引入验前分布的不确定性测度和支持度,提出了基于不确定性测度与支持度相结合的验前信息加权融合方法.首先,利用β分布对测试性验前信息的不确定性进行描述,运用不同的验前信息确定验前分布超参数;然后,引入不确定性测度和支持度作为验前信息加权因子,设计了相应的融合算法;最后利用混合验前分布,结合测试性现场试验数据,计算了Bayes融合评估的验后结果.该方法不仅考虑了验前分布本身对测试性参数的真实情况描述的接近程度,还考虑了不同来源的验前信息之间的支持程度.实例分析表明,在同一置信水平下,基于该方法的测试性评估置信下限相对于传统方法的测试性评估置信下限大约提高了0.7%.      

A novel approach of testability modeling and analysis for PHM systems based on failure evolution mechanism

Prognostics and health management (PHM) significantly improves system availability and reliability, and reduces the cost of system operations. Design for testability (DFT) developed concurrently with system design is an important way to improve PHM capability. Testability modeling and analysis are the foundation of DFT. This paper proposes a novel approach of testability modeling and analysis based on failure evolution mechanisms. At the component level, the fault progression-related information of each unit under test (UUT) in a system is obtained by means of failure modes, evolution mechanisms, effects and criticality analysis (FMEMECA), and then the failure-symptom dependency can be generated. At the system level, the dynamic attributes of UUTs are assigned by using the bond graph methodology, and then the symptom-test dependency can be obtained by means of the functional flow method. Based on the failure-symptom and symptom-test dependencies, testability analysis for PHM systems can be realized. A shunt motor is used to verify the application of the approach proposed in this paper. Experimental results show that this approach is able to be applied to testability modeling and analysis for PHM systems very well, and the analysis results can provide a guide for engineers to design for testability in order to improve PHM performance.     

基于优化SPOT和D-S证据理论的测试性验证方案

针对现有基于序贯验后加权检验的测试性验证方案对测试性设计指标之间的模糊参数空间考虑不足,以及未能充分运用测试性多源先验信息的问题,提出一种优化序贯验后加权检验和D-S证据理论相结合的测试性验证方案。首先,考虑测试性设计指标之间的模糊参数空间,构建三参数空间复杂假设,并基于Bayes理论研究序贯决策规则,同时确定决策因子以及决策阈值;其次,以测试性指标构成的参数空间为辨识框架,分别构造基于专家信息以及测试性试验数据等先验信息的基本信任分配函数,建立融合多源先验信息的优化序贯验证方案;最后,结合实例进行研究,并与经典验证方案、传统Bayes验证方案、序贯概率比检验方案以及序贯验后加权检验方案进行了对比分析。结果表明,该方案由于考虑了模糊参数空间以及充分融合了多源先验信息,有效解决了模糊参数空间的处理问题,同时所确定的平均故障样本量在决策支持的参数空间均优于其他方法。     

基于竞争性试验的通用化保障设备选型评估方法研究

保障设备通用化是航空装备系统减小保障规模、发挥最大保障效能的重要途径。通用化保障设备选型则是通过在真实的使用环境开展初始试用和评价,在备选型号中优选出合格供应商、适用的型号。对于航空装备系统的保障能力需求,首先构建通用化保障设备能力评估指标体系;其次,分析竞争性试验的设计需求和原则,设计适用于外场评估的试验方案和流程。同时,给出可操作性评估准则转化的一般过程,形成基于关联度的统型竞标试验权重确定方法。应用表明:该方法能够大幅提高我国航空统型保障设备面向多机型对接的试验流程的规范化,缩短试飞周期,具有重大的军事和经济效益。     

基于能量法的起落架落震试验评定准则

为通过理论分析建立一套用于起落架落震试验评定的基本准则,提出了一种使用起落架缓冲系统设计要求或其等效形式进行落震试验评定的方法,并从能量分析的角度给出了适用于陆基飞机起落架落震试验评定的统一设计要求。对于在落震试验中无法直接验证的耗能设计要求,通过能量等效的方法,研究了不同落震试验方法中的等效形式。对于仿升法落震试验,提出了利用反行程阻尼系数进行耗能评定,并建立了反行程阻尼系数与缓冲系统消耗能量之间的函数关系。在此基础之上,结合正反行程时间的限制条件,给出了耗能极值问题的计算方法。对于减缩质量法落震试验,建立了缓冲系统耗能系数和机轮不跳离地面之间的联系,研究了随过载增大实现机轮不跳离地面的可行性。最后,研究了两种落震试验方法的能力范围,并给出减缩质量法和仿升法等效的条件。     

小样本无失效寿命试验数据的轴承可靠性评估

针对小样本无失效寿命试验数据可靠性问题提出了评估模型。模型采用Bayes理论构造服从原始样本的抽样函数,结合Bootstrap法生成大量服从抽样函数的随机数作为增广样本,再通过最佳线性不变估计法分析原始样本及增广样本得到Weibull分布双参数估计值作为可靠性评估结果。通过Monte-Carlo法仿真生成服从Weibull分布的随机数,分别采用该模型、配分布曲线法及现有Bayes理论对此随机数做评估,对比发现:该模型得到的参数估计较现有Bayes理论和配分布曲线法更接近Weibull双参数真值,且形状参数和尺度参数估计值的相对误差均低于10%,验证了模型分析小样本无失效数据进行可靠性评估的可行性。借助文献实例对模型进行分析,对比得出模型能得到较现有Bayes理论和配分布曲线法更符合工程实际的评估结果;模型在小样本情况下的双侧可靠度置信区间长度低于现有Bayes理论和配分布曲线法,有效提高了小样本无失效数据可靠性评估精度。