伺服机构模型参数辨识方法研究

主要研究了某型伺服机构模型在频率域的辨识方法。根据实测的伺服机构幅、相频率特性 ,采用了改进的levy曲线拟合辨识方法 ,得到了伺服机构传递函数模型 ,并对辨识结果进行了误差评估。结果表明 ,该方法简单、有效 ,可满足实际应用中的精度要求     

舵面-液压伺服机构连接刚度参数辨识

应用特征方程反问题的直接方法对舵面－液压伺服机构连接刚度参数进行了辨识。方法以动柔度矩阵特征方程为基础，通过界面位移求解界面内力，并由模态迭加法通过舵面上可测自由度振型，拟合扩充机构内部的不可测自由度振型，然后由界面位移和内力确定连接部位的刚度参数，对某导弹舵面－液压伺服机构建模，并辨识相应界面的连接参数，结果表明，该方法简便且精度高，为舵面－液压伺服机构的动力学建模和分析提供了有效方法。     

一种估计线性调频信号参数的方法

合成孔径雷达实际发射的脉冲信号并非标准的线性调频信号 ,而是带有高次相位误差的调频信号。在高次相位误差较大的情况下 ,将对成像质量产生影响。因此 ,必须对发射信号的线性调频项和高次相位误差进行测试。文中提出利用一维相位解缠和多项式拟合测试发射脉冲信号参数的方法 ,仿真结果表明 ,具有较高的估计精度和较好的实用性     

线性回归模型的最小均方误差估计

在未知线性回归模型测量误差的协方差矩阵和非零均值(由非模型化误差及测量设备系统性误差组成)情况下,提出一种回归参数的“最小均方误差估计“,证明了其优良性。还对稳健估计、测量精度分析中随机与系统性误差分离、白塞尔公式与变量差分法统计随机方差结果不一致等问题,作了深入研究分析。     

挠性空间结构变形的自适应辨识

本文以空间控制中的挠性结构变形的辨识为背景,以李雅普诺夫稳定性理论为基础,从辨识的一致性原则出发,给出时变参数的自适应辨识算法。该算法具有梯度型递推形式,结构简单、容易实现。计算机模拟结果表明该算法是解决时变参数辨识的一种有效方法。     

充分统计量在数字信号处理中的应用研究

分析了充分统计量在数字信号处理中的应用,简述了充分统计量的理论模型,重点研究了充分统计量在高斯信道中的应用,结合具体的实例对传统意义下的基于贝叶斯准则的估计和基于充分统计量的估计的性能进行了比较分析;分析比较了基于充分统计量的估计与传统的基于线性模型估计的一致性,全文以具体简洁的实例,针对充分统计量理论用于信号数字参数的估计问题提供了参考。     

自抗扰技术在船载天线伺服系统中的应用研究

为减小船摇扰动对船载天线伺服系统指向及跟踪精度的影响，引入线性自抗扰控制器（LADRC）对伺服系统位置环进行改进。首先对天线伺服系统模型进行简要分析，建立系统状态空间方程；然后利用LADRC对系统进行改进，并对其参数设计进行了详细介绍，同时为提高系统动态跟踪性能，利用TD微分器提取目标速度信息进行前馈补偿；最后经实验测试验证，LADRC相对于传统PID控制器能够保持天线伺服系统动态性能不下降，同时有效提高系统的抗船摇性能。     

Real-time fault detection method based on belief rule base for aircraft navigation system

Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults. On account of this reason, we propose an online detection solution based on non-analytical model. In this article, the navigation system fault detection model is established based on belief rule base (BRB), where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output. To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update, a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization (EM) algorithm. Furthermore, the proposed method is verified by navigation experiment. Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model. The output of the detection model can track the fault state very well, and the faults can be diagnosed in real time and accurately. In addition, the detection ability, especially in the probability of false detection, is superior to offline optimization method, and thus the system reliability has great improvement.     

Optimization on conventional and electric air-cycle refrigeration systems of aircraft: A short-cut method and analysis

The air-cycle refrigeration system is widely used in commercial and military aircraft, and its efficiency greatly affects aircraft performance. Nowadays, this system requires a more efficient design and optimization method. In this paper, a short-cut optimization method with high efficiency and effectiveness is introduced for both conventional and electric air-cycle refrigeration systems. Based on the system characteristics, a four-layer parameter matching algorithm is designed which avoids computational difficulty caused by simultaneous equations. Fuel penalty is chosen as the objective function of optimization; design variables are reduced based on sensitivity analysis to improve optimization efficiency. The results show that the 3-variable optimization of the conventional air-cycle refrigeration system can obtain almost the same results as the traditional 6-variable optimization in that these two optimizations can both significantly reduce the fuel penalty. However, the computer running time of the 3-variable optimization is much shorter than that of the 6-variable optimization. The optimal fuel penalty of the electric air-cycle refrigeration system is lower than that of the conventional one. This study can provide reference for optimizing the air-cycle refrigeration system of aircraft.     

A novel none once per revolution blade tip timing based blade vibration parameters identification method

The vibration caused blade High Cycle Fatigue (HCF) is seriously affects the safety operation of turbomachinery especially for aero-engine. Thus, it is crucial important to identify the blade vibration parameters and then evaluate the dynamic stress amplitude. Blade Tip Timing (BTT) method is one of the promising method to solve these problems. While, it need a high resolution Once Per Revolution (OPR) signal which is difficult to get for the aero-engine. Here, a Coupled Vibration Analysis (CVA) method for identifying blade vibration parameters by a none OPR BTT is proposed. The method assumes that every real blade has its own vibration performance at a given speed. Whereby, it can take any blade as the reference blade, and the other blades using the reference blade as the OPR for vibration displacement calculating and further parameter identifying. The proposed method is validated by numerical model. Also, experimental studies are carried out on a straight blade and a twisted three dimensional blade test rig as well as a large industrial axial compressor respectively. The results show that the proposed method can accurately identify the blade synchronous vibration parameters and quantitatively evaluate the mistuning in bladed disks, which lays a foundation for the reliability improvement of aero-engine.