Defect Recognition in Thermosonic Imaging

This work is aimed at developing an effective method for defect recognition in thermosonic imaging.The heat mechanism of thermosonic imaging is introduced,and the problem for defect recognition is discussed.For this purpose,defect existing in the inner wall of a metal pipeline specimen and defects embedded in a carbon fiber reinforced plastic(CFRP) laminate are tested.The experimental data are processed by pulse phase thermography(PPT) method to show the phase images at different frequencies,and the characteristic of phase angle vs frequency curve of thermal anomalies and sound area is analyzed.A binary image,which is based on the characteristic value of defects,is obtained by a new recognition algorithm to show the defects.Results demonstrate good defect recognition performance for thermosonic imaging,and the reliability of this technique can be improved by the method.     

Asymptotic Performance of Sparse Signal Detection Using Convex Programming Method

The detection of sparse signals against background noise is considered. Detecting signals of such kind is difficult since only a small portion of the signal carries information. Prior knowledge is usually assumed to ease detection. In this paper, we consider the general unknown and arbitrary sparse signal detection problem when no prior knowledge is available. Under a Neyman-Pearson hypothesis-testing framework, a new detection scheme is proposed by combining a generalized likelihood ratio test (GLRT)-like test statistic and convex programming methods which directly exploit sparsity in an underdetermined system of linear equations. We characterize large sample behavior of the proposed method by analyzing its asymptotic performance. Specifically, we give the condition for the Chernoff-consistent detection which shows that the proposed method is very sensitive to the 2 norm energy of the sparse signals. Both the false alarm rate and the miss rate tend to zero at vanishing signal-to-noise ratio (SNR), as long as the signal energy grows at least logarithmically with the problem dimension. Next we give a large deviation analysis to characterize the error exponent for the Neyman-Pearson detection. We derive the oracle error exponent assuming signal knowledge. Then we explicitly derive the error exponent of the proposed scheme and compare it with the oracle exponent. We complement our study with numerical experiments, showing that the proposed method performs in the vicinity of the likelihood ratio test (LRT) method in the finite sample scenario and the error probability degrades exponentially with the number of observations.     

Nonlinear Adaptive Robust Force Control of Hydraulic Load Simulator

This paper deals with the high performance force control of hydraulic load simulator. Many previous works for hydraulic force control are based on their linearization equations, but hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative control not yield to high-performance requirements. In this paper, a nonlinear system model is derived and linear parameterization is made for adaptive control. Then a discontinuous projection-based nonlinear adaptive robust force controller is developed for hydraulic load simulator. The proposed controller constructs an asymptotically stable adaptive controller and adaptation laws, which can compensate for the system nonlinearities and uncertain parameters. Meanwhile a well-designed robust controller is also developed to cope with the hydraulic system uncertain nonlinearities. The controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities; in the absence of uncertain nonlinearities, the scheme also achieves asymptotic tracking performance. Simulation and experiment comparative results are obtained to verify the high-performance nature of the proposed control strategy and the tracking accuracy is greatly improved.     

Visualization Experiments of a Specific Fuel Flow Through Quartz-glass Tubes Under both Sub- and Supercritical Conditions

The present work is a visualization study of a typical kerosene (RP-3) flowing through vertical and horizontal quartz-glass tubes under both suband supercritical conditions by a high speed camera. The experiments are accomplished at temperatures of 300-730 K under pressures from 0.107-5 MPa. Six distinctive two-phase flow patterns are observed in upward flow and the critical point of RP-3 is identified as critical pressure pc=2.33 MPa and critical temperature Tc=645.04 K and it is found that when the fluid pressure exceeds 2.33 MPa the flow can be considered as a single phase flow. The critical opalescence phenomenon of RP-3 is observed when the temperature is between 643.16 K and 648.61 K and the pressure is between 2.308 MPa and 2.366 MPa. The region filled by the critical opalescence in the upward flow is clearly larger than that in the downward flow due to the interaction between the buoyancy force and fluid inertia. Morecover, obvious layered flow phenomenon is observed in horizontal flow under supercritical pressures due to the differences of gravity and density.     

中国民航运输系统性测度研究

对民航运输系统发展程度的有效测度是实现民航运输系统协同发展的前提和基础,从民航运输系统性内涵出发,构建了民航运输系统性测度模型。借助数据包络分析评价方法,建立了民航运输系统总体评价方法,基于协同理论建立了民航运输子系统协调度测度模型和方法。并应用所建立的模型和方法,对中国民航运输系统性状况进行了实证研究。研究结果表明,中国民航系统的有效性有待提高,航空公司系统、机场系统与空管系统两两之间均处于中度协调状态,动态协调度呈现出上升趋势。     

基于分层变块大小运动估计的边信息提取算法(英文)

在分布式视频编码(DVC)中,边信息的质量对视频序列的压缩效果有很大影响。本文中,一种基于分层运动估计的边信息提取算法引入到DVC系统中。首先,采用了两种运动估计模式,向前运动估计和双向运动估计,然后利用分层变块大小运动估计算法获得了比较准确的运动矢量。接着运动矢量滤波器修正了由于局部相似造成的错误运动矢量。最后,选择决策模块更好地处理了帧内插技术中的多种估计模式的问题。这些算法为DVC提供了更好的边信息,提高了DVC系统的性能。实验结果显示,基于这种新算法的DVC系统高于传统视频编码帧内模式 3-4dB,而仅仅低于传统视频编码IBIB模式0.5-1dB。     

基于区域分割的红外与可见光图像融合算法的研究(英文)

由于红外图像和可见光图像的成像特点不同,因此在航空监视领域红外图像和可见光图像融合有重要的研究意义。由于非下采Contourlet变换具有更好的方向性、较高的逼近精度和更好的稀疏表达性能,能有效的提取图像的特征信息。因此我们在非下采Contourlet域,以空间频率为度量标准对红外图像进行阈值分割,经过分割将红外图像和可见光图像分别划分为目标区域以及背景,随后对红外图像和可见光图像进行边缘检测从而得到边缘区域,针对三个不同区域分别选择不同的融合规则进行融合。通过两组不同灰度差异的红外与可见光图像的实验,将基于像素点,窗口策略的融合算法和本文所提出基于区域算法进行了主观和客观的对比,试验结果表明基于区域分割的红外与可见光图像融合算法不仅能有效提取出红外图像中的目标信息还能有效的保持可见光图像的所反映的光谱信息,因此本文提出的算法是一种有效且可行的图像融合算法。     

非平行边界层C型失稳的非线性演化(英文)

提出用抛物化稳定性方程(PSE)新方法,研究非平行边界层从层流向湍流转捩的C型失稳的演化过程,特别是非线性演化问题。研究了至关重要的初始条件,包括各扰动谐波的初始解、初始站均流变形的模拟、以及通过对线性 PSE 的求解获得 TS波和C型亚谐扰动的初始站值等。发展了高精度的数值方法,满足PSE的关键性正规化条件,实现非线性抛物化稳定性方程的有效求解和稳定推进。算例展示了Blasius边界层的C型失稳的非线性演化过程,与典型实验结果相吻合。     

辅助工程师设计的知识融合设计方法:卫星舱布局设计(英文)

卫星舱布局设计属工程系统设计问题,为用传统计算方法难以解决的问题,该问题具有三重难度:工程复杂性、计算复杂性和达到工程实用难。卫星布局设计师的成功经验表明,它需要依赖设计师的经验和智慧、借鉴先验知识和辅以"计算"进行设计,并实现人机结合。本文的人机结合方法采用在线人知识、在线计算知识和先验知识(如参考布局施工图)的知识融合方法,并在卫星布局CAD、仿真与评价系统平台上实现,发挥人机各自特长。主要研究:(1)设计知识:包括在线人知识、在线计算知识和先验知识的表达;(2)上述3类知识的广义描述模型及其知识融合方法;(3)人的作用。经以简化的国际通信卫星舱布局设计为例的数值实验验证,表明了本文方法的可行性。