A systematic approach to nonlinear rotorcraft model identification

The development of a powerful parameter estimation routine and its integration into the simulation environment HOST is described. With this tool approaches are being made towards new strategies of mathematical modeling, aimed at providing highly accurate and nevertheless run-time efficient simulation models. The identification routine is capable of optimizing parameterized models in both dynamic time domain simulation and static (e.g. trim state variation) conditions. Examples of both cases are presented to emphasize the improvement in the system response prediction and to demonstrate the abilities of the identification techniques in combination with the nonlinear simulation platform. This article reviews the activities and achievements accomplished by the DLR Institute of Flight Research and the ONERA Systems Control and Flight Dynamics Department during the last few years in the research on rotorcraft flight dynamics modeling and model identification. Future activities that require extensive high fidelity modeling are in the scope of the current and coming modeling activities that include the use of the presented methods and software technologies.     

挠性空间结构的H∞辨识

重点研究挠性空间结构的Ｈ∞辨识，研究表明：依据系统的输入输出空间，对系统的未知动力学参数估计和对高维数截断的适当操作，将导致适合于控制的低维数学模型。模型维数确定时，系统模型与实际系统的距离在Ｈ∞范数的意义下几乎为最小，模型维数足够大时，系统模型与实际系统的距离可任意小，这是文下间提出了挠性空间结构Ｈ∞辨识的基本思想，为此，以带挠性梁的卫星系统为背景，首先分析了系统的动力学特性，引入了挠性系统Ｈ∞     

藜蒿中绿原酸溶剂提取方法研究

应用醇溶剂回流法提取藜蒿中绿原酸，通过正交试验，对藜蒿中绿原酸进行溶剂提取条件的优化研究，并分剐讨论了各因素对绿原酸提取率的影响。实验表明，乙醇浓度70％、12倍的提取剂用量、温度85℃、提取时间4h、提取两次为乙醇溶剂提取藜蒿中绿原酸的最佳条件，总绿原酸提取率为1.24％。     

基于虚拟仪器的切削力监控技术研究

研制了一种基于虚拟仪器界面、供现场使用的高精度、高效率的金属切削过程监控系统。研究中采用回归分析、叠加原理及抛物线插值的方法建立切削力模型 ,并基于该模型进行参数估计来提取切削状态特征 ,进而监控整个切削过程     

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.     

Spatial transformation of general sampling-aliasing frequency region for rotating-blade parameter identification with emphasis on single-probe blade tip-timing measurement

Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades. Blade-Tip Timing (BTT) is considered as the most promising technique for operational blade-vibration monitoring, which obtains the parameters that characterize the blade condition from recorded signals. However, its application is hindered by severe undersampling and stringent probe layouts. An inappropriate probe layout can make most of the existing methods invalid or inaccurate. Additionally, a general conflict arises between the allowed and required layouts because of arrangement restrictions. For the sake of economy and safety, parameter identification based on fewer probes has been preferred by users. In this work, a spatial-transformation-based method for parameter identification is proposed based on a single-probe BTT measurement. To present the general Sampling-Aliasing Frequency (SAFE) map definition, the traditional time–frequency analysis methods are extended to a time-sampling frequency. Then, a SAFE map is projected onto a parameter space using spatial transformation to extract the slope and intercept parameters, which can be physically interpreted as an engine order and a natural frequency using coordinate transformation. Finally, the effectiveness and robustness of the proposed method are verified by simulations and experiments under uniformly and nonuniformly variable speed conditions.     

单幅图像的三维重构视觉系统特征点提取算法的研究与实现

实现基于单幅二维图像不标定欧氏重构三维场景的关键技术之一是有效提取彩色伪随机编码图像特征角点。为给图像特征点匹配提供更多的样本信息,采用定位于彩色图像Harris算子探测特征角点,并动态给出角点响应的自适应阈值条件。特征点提取实验及三维欧氏重构结果证实了该方法的适用性和有效性。     

铝颗粒云燃烧研究进展

为探究铝颗粒云燃烧特性,把握其研究进展,并为后续研究工作提供参考,本文首先简述了铝颗粒点火、燃烧过程,总结了铝颗粒燃烧机理;其次,综述了铝颗粒云燃烧的实验、理论和模拟研究进展,从不同维度分析了影响颗粒云火焰速度的关键参数,并提出颗粒云燃烧的研究方向,包括提升颗粒云燃烧实验颗粒分散均匀性与表征精度、降低火焰传播速度等实验结果散差、改善颗粒云燃烧理论预测模型精度及构建实用的颗粒云燃烧模拟CFD模型。     

空间目标快速轮廓特征提取与跟踪技术

为满足空间目标交会对接任务中高精度、快速的测量要求,提出了一种空间目标快速轮廓特征提取与跟踪技术。该算法首先从初始帧图像中分割定位目标所在局部区域,作为目标连续跟踪的初始值;其次基于初始帧目标局部区域完成对初始帧目标边缘特征的检测及细化处理;最后采用Hough变换完成对初始帧目标边缘的检测及细化后的局部图像轮廓直线的提取,分别选取目标轮廓四方向最优的直线参数作为最终目标轮廓直线获取的效果,并采用梯度最大法则实现两两求交获取的轮廓特征的优化提取。在目标逼近过程中,结合相邻帧图像间目标尺度动态变化的关联性,根据初始帧提取目标轮廓特征的先验信息,确定目标在第二帧图像中的轮廓位置,并依次根据上一帧图像的轮廓位置信息定位目标在当前帧所在的区域,通过局部处理实现序列图像轮廓区域特征的连续跟踪。该算法无需遍历整个图像,所需处理的目标区域大幅减小,能够有效克服由目标图像较多边缘干扰导致的轮廓提取效果差及处理速度慢的缺点,具有速度快、准确性强、稳定性高等优点。     

Inertial parameter estimation and control of non-cooperative target with unilateral contact constraint

In this paper, the relative sliding motion between the target and the manipulator’s end-effector is considered and characterized as a unilateral contact constraint. A new possible solution is presented to estimate the inertial parameters of a non-cooperative target while the relative sliding motion exists. First, the detailed analysis of the dynamical model is presented, and a parameter-explicit linear time-varying model is obtained. Then, an extended state observer is constructed based on the new model, which can effectively estimate the unknown inertial parameters of the target when relative sliding motion exists. As the modified reactionless controller requires the knowledge of inertial parameters, a hybrid post-capture control scheme is also established based on the switch law between different controllers. The correctness and efficiency of the proposed algorithm are validated by numerical simulation, which proves a potential framework for the non-cooperative target post-capture operation.