某型通航飞机失速警告失效故障分析

针对某型通航飞机地面测试中发现失速警告不工作的故障,分析该失速警告系统各组成部分的结构、原理、功能、走线,制定具体排故程序逐步判断查找出故障原因电子线路故障,并对故障原因进行了分析。     

基于CFD/CSD耦合的叶轮机叶片失速颤振计算

为了研究叶轮机叶片的失速颤振特性,发展了一种计算流体力学与计算结构力学(CFD/CSD)时域耦合方法。该方法通过每一物理时刻CFD和CSD的循环迭代实现了耦合计算。在CFD分析中,采用鲁棒性较好的空间离散格式AUSM+-UP,并基于延迟脱体涡模型(DDES)模拟了带分离流动。在结构分析中,通过模态法构建了旋转叶片动力学方程并运用杂交多步方法进行求解。以孤立转子Rotor37为例,计算了不同工况下流场总体与细节参数,与实验结果的对比验证了CFD算法的精度。对某转子叶片进行了颤振特性研究,计算所得的广义位移时间响应曲线表明该叶片在近失速工况下会发生失速颤振,其表现形式为一阶弯曲模态发散且各阶模态之间不耦合。分析表明,流场不稳定和非定常效应是引起失速颤振的关键因素,同时折合频率的降低也会导致原本气动弹性稳定的叶片发生失速颤振。     

TVC/PSM飞机的过失速动态边界及敏捷性分析

以飞机为质点，考虑在最少输入数据情况下，曲于转弯速率图并从能量的角度计算和分析了TVC/PSM飞机的过失速动态边界，选取敏捷性尺度空战周期时间和指向裕度，对比分析了TVC/PSM飞机和传统飞机的敏捷性，得出了一些有益的结论，并提出了一些建议。     

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。     

Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging

Rotating machinery is widely applied in industrial applications. Fault diagnosis of rotating machinery is vital in manufacturing system, which can prevent catastrophic failure and reduce financial losses. Recently, Deep Learning (DL)-based fault diagnosis method becomes a hot topic. Convolutional Neural Network (CNN) is an effective DL method to extract the features of raw data automatically. This paper develops a fault diagnosis method using CNN for InfRared Thermal (IRT) image. First, IRT technique is utilized to capture the IRT images of rotating machinery. Second, the CNN is applied to extract fault features from the IRT images. In the end, the obtained features are fed into the Softmax Regression (SR) classifier for fault pattern identification. The effectiveness of the proposed method is validated using two different experimental data. Results show that the proposed method has a superior performance in identification various faults on rotor and bearings comparing with other deep learning models and traditional vibration-based method.     

Direct position determination using single moving rotating linear array: Noncoherent and coherent processing

To improve the resolution and accuracy of Direct Position Determination (DPD), this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array (RLA). Firstly, the geometry of the RLA is formulated and analysed. According to its geometry, the intercepted noncoherent signals in multiple interception intervals are modeled. Correspondingly, the MUltiple SIgnal Classification (MUSIC) based noncoherent DPD approach is proposed. Secondly, the synchronous coherent pulse signals are individually considered and formulated. And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals. Besides, we also derive the constrained Cramér-Rao Lower Bound (CRLB) expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known. At last, computer simulations are included to examine the performance of the proposed approach. The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation. In addition, coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.     

Stall flutter prediction based on multi-layer GRU neural network

The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model (ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit (GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation (LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.     

三角翼过失速非定常洞壁干扰修正

分别以固壁条件和洞壁附近实测的压力分布,模拟各类实壁和透气壁试验段的洞壁边界条件,利用N-S方程数值求解模型在风洞中的绕流场,得出洞壁干扰对跨音速模型绕流的影响和气动力修正结果。初步研究结果表明,该方法能较有效地模拟模型在跨音速风洞中的绕流场,GBM04A模型在0.6m风洞中的试验结果经洞壁干扰修正后与无干扰参考结果吻合较好     

轴流风扇旋转失速时的流场测量与分析

针对渐近型旋转失速在一轴流风扇上进行了一些测量工作,包括失速时的激光平均流场测量和热丝动态测量两大类。激光平均流场研究表明失速团主要活动在风扇转子前缘,而转子叶片通道中的流场则主要表现为叶尖间隙流的横向堵塞流动。      

合成射流控制NACA0015翼型大攻角流动分离

为了研究合成射流激励器处于NACA0015翼型回流区时对其分离流动的控制,采用商用计算流体力学软件Fluent 6.1求解Reynolds平均Navier-Stokes方程,通过对翼型气动力特性、脱落漩涡结构以及射流孔口附近流动结构的分析,揭示了合成射流处于分离区时对边界层控制的机理.结果表明:当合成射流孔口处于回流区时仍可有效推迟翼面边界层分离点,缩小回流区范围,从而有效提高翼型的升力.当射流方向垂直于壁面,无量纲频率以及吹气速度比都等于1时,翼型平均升力系数提高40%左右.