Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

基于变刚度变阻尼的柔性喷管动态模型

针对柔性接头动态迟滞曲线受控制系统控制位置精度和动态响应速度影响较大的问题,基于电液伺服机构和柔性接头变刚度变阻尼模型,构建了柔性喷管的电液伺服机构-变刚度变阻尼模型,将其和电液伺服机构-定刚度定阻尼模型进行了对比。分析了电液伺服机构主要参数、柔性接头工作参数等对电液伺服机构-柔性接头系统动态特性的影响。分析结果表明:电液伺服机构-变刚度变阻尼模型所构造的迟滞曲线可更准确地与实验结果相吻合,并符合迟滞曲线随频率变化的规律,反馈系数、放大器静态放大系数、电液伺服机构增益、滑阀流量增益等参数对系统动态特性的影响更为明显。该模型为固体火箭发动机电液伺服机构-柔性接头系统动态特性的调整提供理论依据。     

变体辅助的无人机栖落机动模糊控制设计

无人机（Unmanned aerial vehicle， UAV）的栖落机动是一种大幅度的俯仰运动，易引起升降舵操纵力矩饱和。本文以变体方式增强无人机的俯仰操纵能力，并研究其对应的控制设计方法。首先对栖落机动建立了纵向动力学模型，并通过采用轨迹线性化和张量积变换方法转换得到T-S模糊模型。基于Lyapunov稳定理论和平方和方法，设计了满足控制输入约束的栖落机动多项式模糊控制器。对非变体与变体下的栖落机动控制过程进行了仿真，结果验证了控制律的有效性，并且表明变体辅助的无人机具有更强的操纵性能，能提高栖落机动中升降舵的抗饱和能力。     

移15°双十二相隐极同步整流发电机数学模型的研究

分别在abc坐标系和dq0坐标系下建立了移15°双十二相隐极同步整流发电机的基本数学方程,推导了电机电压、磁链、输出功率、电磁转矩和转子运动方程。在MATLAB/Simulink中建立了移15°双十二相隐极同步整流发电机的仿真模型。对两路输出进行了不平衡负载仿真和试验。仿真与试验结果相比基本一致,验证了移15°双十二相隐极同步整流发电机数学模型的正确性。这为双十二相同步整流发电机运行性能和励磁控制系统的研究奠定了基础。     

Fault diagnosis based on measurement reconstruction of HPT exit pressure for turbofan engine

Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.     

考虑测试性设计缺陷修正延时的测试性增长模型建模与评价方法

针对现有测试性增长模型忽略了测试性设计缺陷的修正延时过程，进而导致测试性增长模型（TGM）跟踪与预计精度低的问题，提出了一种考虑测试性设计缺陷修正延时的测试性增长模型建模理论与方法。首先分析测试性设计缺陷识别与修正之间的延时机理，得到剩余测试性设计缺陷（TDL）具有先增后减的铃形变化趋势；在此基础上，分别以Gamma、Raleigh和Delay-S 3种曲线拟合剩余测试性设计缺陷（RTDL）变化趋势，研究建立基于以上3种曲线考虑修正延时的测试性增长模型；最后，以某机载稳定跟踪平台测试性增长试验数据验证测试性增长模型拟合、跟踪及预计效能。研究结果表明：基于该测试性增长试验数据，Gamma曲线可以精确地拟合剩余测试性设计缺陷变化规律，测试性增长模型跟踪和预计精度可达到10^-2数量级。     

基于室内无线模型的穿墙损耗校正

K-M（Keenan-Motley）模型将单墙固定损耗值相加来计算室内无线信号穿透多墙的总损耗值，存在较大误差。针对该问题选取多种室内场景分别进行连续波（Continuous Wave，CW）测试，对无线信号穿墙损耗的影响因素和变化规律进行分析，提出了一种基于人工神经网络的室内无线模型穿墙损耗校正方法，对预处理后的测试数据进行训练并建立预测模型。经验证该预测模型符合校正判别准则，在实际场景下具有良好的预测准确度。     

哨兵2卫星综合水质指标的河流水质遥感监测方法

上海市河流水污染监测是当前研究的热点问题。针对上海市河流水质监测的需求,提出了一种基于因子分析的河流综合水质遥感反演的方法。以欧洲航空局发射的哨兵-2A(Sentinel-2A)卫星搭载的多光谱成像仪获取的遥感影像,以及准同步获取的河流断面实测水质参数数据为例,研究对象为上海市青浦区和松江区部分河道。选取高锰酸盐指数、氨氮等5项主要水质参数为监测指标,在因子分析的基础上建立水质遥感反演的模型,得到综合水质指标用于确定水质类别。实验结果表明:综合水质指标值越小,内陆河流水质状况越良好,水体更清洁。该方法能够应用于内陆河流水质遥感监测,为水环境管理部门提供参考信息。     

基于两相流模型的挤压油膜阻尼器空化流场特性数值模拟

基于气液两相流理论中的Mixture模型和Zwart-Gerber-Belamri空化模型,采用动网格技术建立了两端开口中心槽供油型挤压油膜阻尼器三维非定常空化流场求解模型。数值模拟表明:随着阻尼器内环进动,考虑两相流动的油膜低压区在中心槽的两侧产生两道对称的条状负压带,条状带内具有较高的气相体积分数;阻尼器低压区的压力和气相体积分数对进油孔位置十分敏感,阻尼器油膜力和流场气穴比的变化频率与进油孔数密切相关。内环同心进动半径、进动频率对阻尼器空化流场影响的数值计算表明,进动半径和频率的增大均会使得流场内的空化现象加剧,同时气穴比的相位滞后现象愈加显著。      

Bayesian network-based extraction of lunar impact craters from optical images and DEM data

Impact craters are among the most noticeable geomorphological features on the planetary surface and yield significant information about terrain evolution and the history of the solar system. Thus, the recognition of impact craters is an important branch of modern planetary studies. Aiming at addressing problems associated with the insufficient and inaccurate detection of lunar impact craters, a decision fusion method within the Bayesian network (BN) framework is developed in this paper to handle multi-source information from both optical images and associated digital elevation model (DEM) data. First, we implement the edge-based method for efficiently searching crater candidates which are the image patches that can potentially contain impact craters. Secondly, the multi-source representations of an impact crater derived from both optical images and DEM data are proposed and constructed to quantitatively describe the two-dimensional (2D) and three-dimensional (3D) morphology, consisting of Histogram of Oriented Gradient (HOG), Histogram of Multi-scale Slope (HMS) and Histogram of Multi-scale Aspect (HMA). Finally, a BN-based framework integrates the multi-source representations of impact craters, which can provide reductant and complementary information, for distinguishing craters from non-craters. To evaluate the effectiveness and robustness of the proposed method, experiments were conducted on three lunar scenes using both orthoimages from the Lunar Reconnaissance Orbiter (LRO) and DEM data acquired by the Lunar Orbiter Laser Altimeter (LOLA). Experimental results demonstrate that integrating optical images with DEM data significantly decreases the number of false positives compared with using optical images alone, with F₁-score of 84.8% on average. Moreover, compared with other existing fusion methods, our proposed method was quite advantageous especially for the detection of small-scale craters with diameters less than 1000 m.