仿生正弦前缘对翼面动态失速的影响

动态失速导致叶片气动载荷急剧变化，造成振动载荷激增，桨叶寿命大幅衰减。针对动态失速问题，从座头鲸胸鳍在动态倾转下取得良好的流动特性获得启示，据此模化出仿生正弦前缘翼面（包含3种波峰和2种波长），旨在实现动态失速控制。借助三维非定常数值模拟方法，采用运动网格技术，基于SC1095旋翼翼型，研究了仿生前缘动态失速流动控制机理及运动参数和来流速度的影响。结果表明：正弦前缘大幅度降低俯仰力矩系数峰值和阻力系数峰值；前缘波峰越大、波长越小，阻力系数峰值与俯仰力矩系数峰值的抑制效果越明显，虽然升力系数峰值减小，但其减小量远小于前两者，例如其中一种仿生翼使俯仰力矩系数峰值减小了47.7%，阻力系数峰值减小了36.4%，升力系数峰值减小14.1%；在最大迎角附近，正弦前缘能够缓和失速特性，使载荷变化更为平缓；在高平均迎角、低俯仰频率、低马赫数下，仿生翼动态失速控制效果更强，相比较而言迎角振幅的影响较小。     

基于IPSO-Elman神经网络的飞机客舱能耗预测

为了提高飞机客舱使用地面空调制冷时客舱能耗的预测精度，提出了一种改进的粒子群优化（IPSO）Elman神经网络的飞机客舱能耗预测模型。依据对算法中惯性权重与学习因子的收敛域分析，得出了二者合理的取值范围，将粒子到全局最优位置间距离与参数的取值范围相结合，构造了惯性权重与学习因子的动态调节函数，对其进行非线性的动态调节，并引入了变异因子，提出了一种跳出局部最优的策略，防止粒子群优化（PSO）陷入局部最优。将IPSO-Elman应用于Boeing738飞机客舱能耗预测中，与PSO-Elman、Elman算法进行性能比较，仿真结果表明基于IPSO-Elman的客舱能耗预测模型在预测精度和收敛速度方面均有一定的提升。该研究结果为飞机客舱能耗预测模型的建立提供了理论依据，对飞机地面空调的节能与机场电能合理调配提供了支持。     

Orbit determination of BDS-3 satellite based on regional ground tracking station and inter-satellite link observations

The BeiDou global navigation satellite system (BDS-3) has established the Ka-band inter-satellite link (ISL) to realize a two-way ranging function between satellites, which provides a new observation technology for the orbit determination of BDS-3 satellites. Therefore, this study presents a BDS satellite orbit determination model based on ground tracking station (GTS) observations and ISL ranging observations firstly to analyze the impact of the ISL ranging observations on the orbit determination of BDS-3 satellites. Subsequently, considering the data fusion processing, the variance component estimation (VCE) algorithm is applied to the parameter estimation process of the satellite orbit determination. Finally, using the measured data from China’s regional GTS observations and BDS-3 ISL ranging observations, the effects of ISL ranging observations on the orbit determination accuracy of BDS-3 satellites are analyzed. Moreover, the impact of the VCE algorithm on the fusion data processing is evaluated from the aspects of orbit determination accuracy, Ka-band hardware delay parameter stability, and ISL ranging observation residuals. The results show that for China’s regional GTSs, the addition of BDS-3 ISL ranging observations can significantly improve the orbit determination accuracy of BDS-3 satellites. The observed orbit determination accuracy of satellite radial component is improved from 48 cm to 4.1 cm. In addition, when the initial weight ratio between GTS observations and ISL ranging observations is not appropriate, the various indicators which include orbit determination accuracy, ISL hardware delay, and ISL observation residuals were observed to have improved after the adjustment of the VCE algorithm. These results validate the effectiveness of the VCE algorithm for the fusion data processing of the GTS observations and ISL ranging observations.     

A new bearing fault diagnosis method based on modified convolutional neural networks

Fault diagnosis is vital in manufacturing system. However, the first step of the traditional fault diagnosis method is to process the signal, extract the features and then put the features into a selected classifier for classification. The process of feature extraction depends on the experimenters’ experience, and the classification rate of the shallow diagnostic model does not achieve satisfactory results. In view of these problems, this paper proposes a method of converting raw signals into two-dimensional images. This method can extract the features of the converted two-dimensional images and eliminate the impact of expert’s experience on the feature extraction process. And it follows by proposing an intelligent diagnosis algorithm based on Convolution Neural Network (CNN), which can automatically accomplish the process of the feature extraction and fault diagnosis. The effect of this method is verified by bearing data. The influence of different sample sizes and different load conditions on the diagnostic capability of this method is analyzed. The results show that the proposed method is effective and can meet the timeliness requirements of fault diagnosis.     

分布式容错配电系统设计与仿真

阐述了分布式容错配电系统的功能需求及构型设计,完成了分布式容错配电仿真验证系统的研制,并进行了试验验证。结果表明:系统运行可靠,控制逻辑正确,系统设计满足功能要求。     

民用飞机全机静力试验前机身工况配平载荷设计

民用飞机全机静力试验中由于加载方案复杂,为了简化试验加载数量,传统的配平方案主要保证考核区的加载准确性,对于非考核区的载荷简化到若干加载点上。对于飞机机身这种薄壁结构,非考核区的配平对考核区影响较大。以某飞机前机身严重工况为例,基于飞机全机有限元模型,研究静力试验的载荷配平方案;通过对比分析态载荷与传统试验态配平载荷方案下的内力解,对传统全机静力试验载荷配平方案进行优化。结果表明：优化后的试验态内力解与分析态内力解基本吻合;对于飞机机身薄壁结构,圣维南原理并不适用,全机静力试验的载荷配平要与真实工况受力情况吻合,才能达到试验验证目的。     

一种基于随机优化算法的民用飞机突风动载荷重建方法

民用飞机突风载荷的准确重建对于飞行安全具有十分重要的意义。基于随机优化算法,提出一种突风动载荷重建方法。首先,基于频域气弹耦合方程,建立一个突风动载荷时域分析模型,其次,引入Hicks-Henne 型函数进行突风速度场的参数化建模,在此基础上,基于随机优化算法对各型函数参数进行迭代寻优,使得优化目标值与测量值一致,最终得到重建后的突风速度及对应的动态响应及载荷。最后,以GTA 模型经历1-cos 形状突风为例进行数值仿真。结果表明：本文提出的突风动载荷重建方法可有效实现突风速度场的识别,进而完成突风动载荷的重建;针对本文算例,过载最大误差为3.5%,载荷最大误差不超过1%。     

基于集成学习模型的飞行学员认知负荷研究

在飞行过程中,飞行员需要在短时间内接收大量信息,并做出正确的判断与决策,而过高的认知负荷会影响其感知、判断、决策等认知过程,进而影响飞行安全。首先通过飞行模拟实验获取飞行学员在执行不同飞行任务时的生理数据;然后通过时域、频域分析等方法提取呼吸和心电信号的特征,并通过统计学方法筛选出能够反映认知负荷水平的指标;最后结合支持向量机、K 最邻近、人工神经网络等方法建立集成学习模型,对飞行学员的认知负荷进行评估,并与单一算法进行对比。结果表明：本文建立的集成学习模型具有较高的准确率,能够更好地反映飞行学员认知负荷水平。     

螺旋桨桨叶1P气动载荷研究

介绍了一种１Ｐ载荷实验研究方法－桨叶应变测试法,首先通过桨叶剖面速度三角形及气动力分析给出了１Ｐ载荷与测量应变的关系,然后通过地面试验和飞行试验进行了验证。试验结果表明,螺旋桨１Ｐ载荷主要由于非对称气流流过桨盘面改变了桨叶剖面速度三角形而引起,迎角,侧滑角的增加,会产生较大的１Ｐ载荷;机动飞行,如快速拉杆,荷兰滚等也会产生较大的１Ｐ载荷。     

航空发动机设计任务循环的选取

由某型发动机的未来使用任务推导了其设计飞行任务剖面和飞行任务混频,然后根据该发动机的高度－速度特性得出了其转速剖面。在该转速剖面下对发动机的压气机盘进行了应力和疲劳寿命计算,由计算结果得出该发动机设计任务循环的选取范围,认为：航空发动机的设计任务循环除0－最大－0、慢车－最大－慢车和巡航－最大－巡航3类循环以外,还应当包括对发动机构件疲劳寿命有较大影响的其它载荷循环,否则将造成设计载荷估计精度大大降低。