涡轴发动机性能退化数学建模研究

分析了航空发动机各部件性能退化原理;分别建立了压气机、燃烧室、涡轮性能退化的部件模型;根据航空自由涡轮式涡轴发动机的工作和使用特点,建立了性能退化的涡轴发动机数学模型;利用该模型,仿真研究了不同部件性能退化对涡轴发动机性能参数的影响。结果表明,建立的模型正确反映了部件退化对涡轴发动机的影响。     

涡轴发动机自适应混合诊断模型高斯加权聚类方法

针对整个飞行包线内涡轴发动机健康参数估计问题,提出基于高斯加权聚类的机载自适应混合模型建立方法.机载自适应混合模型由卡尔曼滤波器和神经网络组成,由于飞行数据样本庞大,采用高斯加权模型对涡轴发动机飞行数据进行实时聚类,利用聚类数据更新神经网络权重,并实现自适应混合模型工作范围的自动扩展.仿真结果表明了该方法的有效性,采用...     

涡轴发动机全状态实时气动热力学数值模拟

应用“外推”法得到了某型涡轴发动机起动状态的部件特性,采用容积法建立了表达发动机热力过程特性的非线性方程组,从而,解决了通常的部件法建模所带来的需要迭代的问题,建立了涡轴发动机全状态的气动热力学实时模型,给出了某发动机工作全过程的数值模拟结果。     

纤维增强涡轮轴结构失效模式分析方法及试验验证

针对连续纤维增强复合材料涡轮轴结构失效模式分析问题,基于宏-细观力学跨尺度分析方法,建立细观力学代表性体积元(RVE)模型,通过编程模拟实现模型的周期性边界条件,计算纤维增强复合材料应力响应,将其均值应力转化为真实应力,确定失效包线。建立连续纤维增强轴结构力学模型,计算轴结构在扭转载荷下的应力响应。通过复合材料层合板主偏轴关系应力转化,将危险单元各方向宏观应力响应计算结果转化到细观力学RVE模型上,即为细观力学RVE模型受载情况。结合细观力学失效边界确定复合材料轴结构危险位置失效模式,当扭转载荷达到5 000～5 500 N·m之间,复合材料最外层即层6(+45°)首先达到基体拉伸失效载荷。开展复合材料轴结构失效模式试验,在扭转载荷达到6 000 N·m时,声发射信号相互叠加,大部分均为中频信号,中频信号多为基体、界面开裂信号。与模拟仿真计算结果对比分析,验证连续纤维增强复合材料涡轮轴结构失效模式分析方法的有效性。利用所建立模型预测了某型发动机低压涡轮轴的失效载荷及失效模式。     

试车数据驱动的涡轴发动机起动过程模型辨识

针对传统的采用解析法建立涡轴发动机起动过程模型复杂的问题,提出了一种基于变步长萤火虫算法优化的有外部输入的非线性自回归网络(CSFA-NARX)的涡轴发动机起动过程模型辨识方法。以涡轴发动机起动过程试车试验数据为数据样本,利用CSFA-NARX网络模型辨识得到涡轴发动机起动过程模型,并采用留一交叉验证方法对辨识模型的性能进行验证。结果表明:得到的辨识模型输出参数,如燃气发生器转速n_g、输出轴转速n_r和涡轮后温度T₄都较好地逼近了试车实测数据,各参数验证样本最大相对误差平均值分别为0.90%、1.51%、和2.01%;在相同训练与验证样本情况下,得到的辨识模型精度优于采用萤火虫算法优化的NARX网络(FA-NARX)、NARX网络和变步长萤火虫算法优化的BP网络(CSFA-BP)模型精度。     

基于部件法的涡轴发动机性能计算模型研究

为研究自由涡轮式涡轴发动机的稳态特性,建立了基于部件法的涡轴发动机稳态特性计算模型,编制了计算程序,并指出了涡轴发动机各部件在共同工作时需要满足的平衡关系,同时建立了求解稳态特性计算模型的非线性方程组。然后利用编制的稳态特性计算程序,计算了某涡轴发动机在考虑使用限制时的最大状态特性和不同高度下的节流特性。通过对计算结果...     

引气冷却模型对涡轴发动机总体性能的影响研究

随着现代涡轴发动机性能的不断提高,其热力循环参数和引气量显著增加。针对这一问题,建立考虑压气机引气位置可变和涡轮中冷却气参与做功的涡轴发动机性能计算模型。当压气机引气位置变化时,采用流量平衡和功率平衡同时修正法计算发动机性能;涡轮冷却计算模型则考虑了第一级导向器叶片冷却气的做功。与传统涡轴发动机性能计算模型的计算结果对比表明:本文的计算模型能够合理反映引气量和引气位置对发动机特性的影响,更接近发动机的真实物理过程,可为发动机空气系统设计提供输入。     

基于QPSO-ELM的某型涡轴发动机起动过程模型辨识

针对解析法建立某型涡轴发动机起动过程模型困难的问题,提出一种基于量子粒子群优化-极限学习机（QPSO-ELM）的某型涡轴发动机起动过程模型数据驱动辨识方法。首先构建基于状态空间法描述的某型涡轴发动机起动过程分段模型,然后结合发动机起动试验数据,采用QPSO-ELM算法对该起动模型进行辨识,试验结果表明：燃气发生器转子转速、发动机输出轴转速和燃气涡轮后温度的辨识结果都良好地逼近了实测数据,最大相对误差的均值分别为1.358%、1.628%和2.195%,满足实际应用的精度需求,并且QPSO-ELM的辨识精度优于极限学习机（ELM）、支持向量机（SVM）和反向传播（BP）神经网络。     

涡轴发动机全状态实时气动热力学数值模拟

用“外推”法得到了某燃气涡轴发动机起动状态的部件特性,采用容积法建立了表达发动机热力过程特性的非线性方程组,解决了通常的部件法建模需要迭代的问题,建立了1个涡轴发动机全状态气动热力学实时模型;在起动建模中考虑了温升对部件效率的影响以及传热对燃气热焓的影响。给出了某发动机从起动到最大状态全过程的数值模拟结果。     

用解析-数值混合法分析层合板的孔边应力

 含圆孔的层合板或各向异性板,在孔内轴销加载下的孔边应力分析,是一个比较复杂的问题。本文提出的解析-数值混合解法,为分析此类问题提供了新的途径。 首先,在作者所建议的力学模型的基础上,建立轴销的柔度方程和孔边等效节点载荷的解析表达式。然后,根据轴销与孔边相接触节点间所应满足的接触条件,综合应用上述解析表达式和有限元素法,建立分析孔边应力的基本方程。-最后,按本文所述递推回代公式进行求解。实例表明,计算结果与实验相符。     

Friction compensation for low velocity control of hydraulic flight motion simulator: A simple adaptive robust approach

Low-velocity tracking capability is a key performance of flight motion simulator (FMS), which is mainly affected by the nonlinear friction force. Though many compensation schemes with ad hoc friction models have been proposed, this paper deals with low-velocity control without friction model, since it is easy to be implemented in practice. Firstly, a nonlinear model of the FMS middle frame, which is driven by a hydraulic rotary actuator, is built. Noting that in the low velocity region, the unmodeled friction force is mainly characterized by a changing-slowly part, thus a simple adaptive law can be employed to learn this changing-slowly part and compensate it. To guarantee the boundedness of adaptation process, a discontinuous projection is utilized and then a robust scheme is proposed. The controller achieves a prescribed output tracking transient performance and final tracking accuracy in general while obtaining asymptotic output tracking in the absence of modeling errors. In addition, a saturated projection adaptive scheme is proposed to improve the globally learning capability when the velocity becomes large, which might make the previous proposed projection-based adaptive law be unstable. Theoretical and extensive experimental results are obtained to verify the high-performance nature of the proposed adaptive robust control strategy.     

微型飞行器过失速降落轨迹跟踪控制设计

采用基于张量积的T-S模糊建模与控制方法,对微型飞行器过失速降落纵向运动的轨迹跟踪控制问题进行了研究。首先,建立了过失速降落中飞行器纵向运动的线性变参数动力学模型;然后,通过张量积模型转化方法,将线性变参数模型转化为张量积胞体模型,基于该模型设计了并行分布补偿控制器,用Lyapunov稳定性理论证明了闭环系统的稳定性,并推导了区域极点配置条件以获得更好的暂态响应性能;最后,对飞行器的过失速降落过程进行了仿真,验证了所设计的跟踪控制器的有效性。     

Geometric error analysis of an over-constrained parallel tracking mechanism using the screw theory

This paper deals with geometric error modeling and sensitivity analysis of an overconstrained parallel tracking mechanism. The main contribution is the consideration of overconstrained features that are usually ignored in previous research. The reciprocal property between a motion and a force is applied to tackle this problem in the framework of the screw theory. First of all, a nominal kinematic model of the parallel tracking mechanism is formulated. On this basis, the actual twist of the moving platform is computed through the superposition of the joint twist and geometric errors. The actuation and constrained wrenches of each limb are applied to exclude the joint displacement. After eliminating repeated errors brought by the multiplication of wrenches, a geometric error model of the parallel tracking mechanism is built. Furthermore,two sensitivity indices are defined to select essential geometric errors for future kinematic calibration. Finally, the geometric error model with minimum geometric errors is verified by simulation with SolidWorks software. Two typical poses of the parallel tracking mechanism are selected, and the differences between simulation and calculation results are very small. The results confirm the correctness and accuracy of the geometric error modeling method for over-constrained parallel mechanisms.     

航空发动机动态链接库模型建模技术研究

针对目前航空发动机组态建模软件不能输出用户所搭建模型的局限性,设计了与组态建模软件相匹配的通用发动机动态链接库模型框架,并将用户在组态建模软件上录入的模型信息输出为1个配置文件,加载该动态链接库模型和配置文件进行发动机仿真,仿真结果与采用组态建模软件所得到的结果一致。通过该方法实现了输出组态建模软件中模型的功能,输出的模型可用于发动机数控系统的设计等工作中。     

Neural network modeling of flight control system

Modeling of angle tracking systems in the presence of actuator non-linearity such as angle, position and rate limits is a very significant and difficult task in the design and implementation of aircraft, target-tracking, and missile guided systems. A new recurrent neural network with time-delayed inputs and output feedback is used for the modeling of angle tracking systems, with emphasis on the neural network architecture, principles and algorithms. The neural network controller with modeling units for angle tracking is designed by using TMS320C25 processors. For time and size requirements, limited precision technology and look-up table technology are used in the design of the hardware and software systems. Given a set of input commands, the network is trained to control the system within the constraints imposed by actuators. The results show that the proposed networks are able to model the angle tracking system through learning without separate consideration of the non-linearity of actuators     

Maximum likelihood track-before-detect with fluctuating targetamplitude

An important problem in target tracking is the detection and tracking of targets in very low signal-to-noise ratio (SNR) environments. In the past, several approaches have been used, including maximum likelihood. The major novelty of this work is the incorporation of a model for fluctuating target amplitude into the maximum likelihood approach for tracking of constant velocity targets. Coupled with a realistic sensor model, this allows the exploitation of signal correlation between resolution cells in the same frame, and also from one frame to the next. The fluctuating amplitude model is a first order model to reflect the inter-frame correlation. The amplitude estimates are obtained using a Kalman filter, from which the likelihood function is derived. A numerical maximization technique avoids problems previously encountered in “velocity filtering” approaches due to mismatch between assumed and actual target velocity, at the cost of additional computation. The Cramer-Rao lower bound (CRLB) is derived for a constant, known amplitude case. Estimation errors are close to this CRLB even when the amplitude is unknown. Results show track detection performance for unknown signal amplitude is nearly the same as that obtained when the correct signal model is used     

飞机装配型架中骨架的数字化设计原理及实现

骨架设计对型架的总体性能和研制进度具有重要的影响。因此,在FixCAD系统的研制中,将骨架的数字化设计方法作为一个主要的问题,开展了专门的研究。但是,由于这些研究未考虑到现在的骨架结构中含有曲轴线和新型材元件的情况,其研究成果已不再适应于这些骨架结构的设计。为此,从对骨架轴线的抽象定义、表示和计算入手,探索和提出全新的骨架数字化设计技术,从根本上解决现有方法存在的局限性。具体包括:(1)根据骨架结构轴线及其设计方法的特点,提出线元、线列和线链等新概念,建立线元逻辑端矢的计算算子;(2)应用所提出的概念和算子,构建骨架的轴线模型、元件端面法矢计算方法、设计过程模型以及元件造型算法等;(3)介绍利用所建立的数据模型和算法技术实现的"骨架数字化设计子系统"及其应用。最后,总结了所介绍的技术特点和意义以及后续研究重点。     

基于自适应Siamese网络的无人机目标跟踪算法

无人机已被广泛应用到军事和民用领域，目标跟踪是无人机应用的关键技术之一。针对无人机跟踪过程中目标易发生形变、遮挡等问题，提出一种基于自适应Siamese网络的无人机目标跟踪算法。首先，利用2个卷积网络构建一个5层Siamese网络，通过对模板特征与当前帧图像特征进行卷积得到目标位置；其次，利用高斯混合模型对以往的预测结果进行建模并建立目标模板库；然后，从模板库中挑选出最可靠的目标模板并以此更新Siamese网络的匹配模板，使Siamese网络能够自适应目标的外观变化；最后，引入回归模型进一步精确目标位置，降低背景对网络性能的影响。仿真实验结果表明：该算法有效降低了形变、遮挡等情况对跟踪性能的影响，具有较高的准确率。     

帧差法和Mean shift算法融合的高速无人机目标跟踪

为实时跟踪高速飞行无人机,图像跟踪算法必须满足快速性和准确性要求。文章给出一个融合算法,将帧差法和 Mean shift算法的优势结合起来。2个算法平行运行,差帧法实现快速跟踪,Mean shift算法则用于对帧差法结果进行准确度修正。还利用 Kalman滤波技术对计算周期内的无人机运动位移进行补偿,进一步提高实时跟踪的准确性,并给出 Matlab仿真例子验证本文方法的有效性。     

BUILDING A UNIFIED PRODUCT MODEL WITH COMPLEX METHOD

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