全局灵敏度分析的支持向量机方法

结构全局灵敏度分析中存在隐式极限状态函数和高计算量困难问题,提出支持向量机和蒙特卡洛方法相结合的一种新的全局可靠性灵敏度分析方法。该方法采用支持向量机拟合输入变量与输出响应之间的关系,同时采用均匀映射得到更多数量的失效样本以获得高精度的代理模型,故仅需少量样本即可将隐式极限状态函数显式表达,与直接蒙特卡罗方法相比,可显著提高计算效率。数值算例和工程算例表明所提方法具有一定的工程应用价值。     

运动补偿用惯性器件误差对SAR成像分辨率的影响研究

 为提高合成孔径雷达（SAR）系统的性价比,必须根据SAR成像分辨率的要求和整体系统参数,设计相应精度的运动补偿用捷联惯导系统。在确定SAR运动补偿系统方案和安装方式的基础上,分析不同方向的加速度计和陀螺仪误差对天线相位中心位置测量误差的影响,并利用位置测量误差与SAR成像分辨率之间的关系,进一步明确了不同方向的加速度计和陀螺仪对SAR成像分辨率的影响。研究表明：基于SAR的工作原理和安装方式,x方向加速度计和y方向陀螺仪对SAR成像分辨率的影响明显比其他惯性器件严重;相同误差水平的惯性器件对SAR成像分辨率的影响随着合成孔径时间和工作波长的不同而不同,时间越长,波长越短,影响则越严重。SAR成像仿真证明了结论的正确性。研究结果对于研制高性价比SAR成像运动补偿系统有一定的理论指导意义。     

非线性二元机翼气动弹性近似解析研究

 建立了不可压流动中多项式迟滞非线性二元机翼的气动弹性运动方程,然后利用谐波平衡法进行了求解。与数值积分结果比较分析表明,在系统发生二次分叉以前,谐波平衡法可以准确地预测极限环振荡的频率和振幅,通过频谱分析与时间响应历程讨论了谐波平衡法产生误差的原因。另外还研究了弹性轴位置对颤振特性的影响,随着弹性轴不断靠近翼弦中点,俯仰振幅不断增大,而沉浮振幅则存在一个极小值点。     

A Polynomial Prediction Filter Method for Estimating Multisensor Dynamically Varying Biases

The estimation of the sensor measurement biases in a multisensor system is vital for the sensor data fusion. A solution is provided for the estimation of dynamically varying multiple sensor biases without any knowledge of the dynamic bias model pa- rameters. It is shown that the sensor bias pseudomeasurement can be dynamically obtained via a parity vector. This is accom- plished by multiplying the sensor uncalibrated measurement equations by a projection matrix so that the measured variable is eliminated from the equations. Once the state equations of the dynamically varying sensor biases are modeled by a polynomial prediction filter, the dynamically varying multisensor biases can be obtained by Kalman filter. Simulation results validate that the proposed method can estimate the constant biases and dynamic biases of multisensors and outperforms the methods reported in literature.     

钢筋砼轴对称扁壳基于双剪屈服准则的极限分析的塑性屈服线方法

文章利用基于双剪屈服线准则所导出的钢筋砼壳体的屈服条件，并利用塑性屈服线方法求解钢筋砼轴对称双曲扁壳在竖向荷载下的极限载荷。     

二项分布参数整体推断方法

针对工程中常见的二态数据,提出了二项分布参数整体推断方法,该方法可以很好地确定二项分布参数与状态变量之间的数学关系式,给出了整体推断的点估计和置信限、置信区间估计公式。它能够将不同状态下的二态数据作为一个整体来进行统计推断,全面开发利用了不同状态下二态数据之间相互提供的横向信息,从而使其可利用的信息量远远大于只能分别在各自状态下对二态数据进行统计分析的传统方法。所以,在精度相同的情况下,可以节省大量试样;而在试样数一定的条件下,又能提高预测精度。最后给出了应用实例。     

Analysis of the code and phase between-receiver inter-system biases of the overlapping frequencies for GPS/Galileo/BDS

The overlapping-frequency signals from different GNSS constellations are interoperable and can be integrated as one constellation in multi-GNSS positioning when inter-system bias (ISB) is properly disposed. The look-up table method for ISB calibration can enhance the model strength, maximize the number of integer-estimable ambiguities, and thus is preferred. However, the characteristics and magnitudes of the receiver code ISB and phase fractional ISB (F-ISB) are not well known and the wrong values of the biases can seriously degrade the positioning results. In this contribution, we first estimate the between-receiver code ISB and phase F-ISB of hundreds of the baselines up to around 25km in the European Permanent GNSS Network (EPN) and the Multi-GNSS Experiment (MGEX) for the overlapping frequencies L1-E1 (L1), L5-E5a (L5) and E5b-B2b (L7). The data collected from 1st January 2016 to 1st January 2019. Second, the receiver-type and firmware-version combinations for the receivers of Trimble, Leica, Javad, Septentrio and NovAtel are carefully classified. Results show that the Septentrio receivers have consistent code and phase ISB values for the three overlapping frequencies i.e. only one value for each frequency and no receivers are different. The Leica, Trimble and Javad receivers have two or more ISB values for at least one of the three frequencies. A few receivers with biases to the groups are also found and listed. Third, the code ISB and phase F-ISB of the groups are adjusted by the least-squares method. The root mean square errors (RMSE) of the least square adjustment are 0.240 m, 0.250 m and 0.200 m for code of L1, L5 and L7 frequencies, respectively, and are 0.0009 m, 0.0015 m and 0.0031 m for phase of L1, L5 and L7 frequencies, respectively. Finally, the effects of code ISB errors on code positing are investigated with the zero-baseline MAT1_MATZ. The distance root mean square error (DRMS) of L1-E1 code positioning can be reduced by 48.2% with 5 GPS and Galileo satellites and the DRMS degrades quickly when the code ISB error is larger.     

Hybrid method based on flame volume concept for lean blowout limits prediction of aero engine combustors

The Lean Blowout (LBO) limit is crucial for the aircraft engines. The semi-empirical (such as Lefebvre’s LBO model and Flame Volume (FV) model), numerical and hybrid methods are widely utilized for the LBO limit quick prediction. An innovative hybrid method based on the FV concept is proposed. This method can be classified as a semi-empirical/physical based hybrid prediction method. In this hybrid method, it is assumed that the flame volume varies nearly linearly with the fuel/air ratio near the LBO. The flame volume is obtained directly by the numerical simulation using the threshold value of the visible flame boundary as 900 K. Then the final LBO limits is determined by the FV model. On the premise of keeping the good generality of prediction, the hybrid method based on the FV concept can further improve the prediction accuracy. The comparison with the prediction of the existing available methods on fifteen combustors shows that the hybrid method based on the FV concept achieves better prediction accuracy. The prediction uncertainties between the experimental results and the predicted values by the hybrid method based on the FV concept are within about ±10%.     

基于最小熵准则的频偏估计算法研究

提出了一种基于SEM(Spectrum Entropy Minimization,频谱熵最小化)的频偏估计算法。研究发现,频偏越小,离散信号频谱的熵越小。根据这一性质建立了相关算法,通过一维搜索的方式得到使相位补偿后信号频谱熵最小的频偏估计。仿真结果表明:SEM算法的估计性能能够达到CR(Cramer-Rao,克拉美罗)下界,而且估计的稳定性和鲁棒性较好,具有一定的应用价值。     

旋转调制光纤陀螺惯导寻北精度探索

高精度寻北是旋转调制光纤陀螺惯导实现高精度导航的前提,也是其技术优势的体现。针对当前旋转调制光纤陀螺惯导在快速高精度寻北中遇到的问题,对其寻北精度极限进行了深入研究,梳理出4项最主要的影响因素,对其影响机理、误差模型、量级进行了深入的分析,并通过样机试验进行了验证。结果表明,尽管随机游走系数是制约寻北精度极限的最终因素,但陀螺刻度系数误差、扰动速度、航向效应等误差处理不好,将严重影响旋转调制寻北精度;通过采取措施,高精度光纤陀螺旋转调制惯导5min寻北精度已达到35″(3σ),进一步提高精度的措施正在研究中。