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。     

一种基于三正交主轴平面的快速星图模拟方法

为在地面上进行星图模拟以测试星图识别算法和星敏感器性能, 提出了一种新的快速星图模拟方法. 该方法利用截面圆和固定区域的性质, 将单位天球按照三个正交主轴平面进行等分, 根据赤纬值求解恒星矢量与主轴平面夹角来确定选星条件, 进而根据坐标变换原理进行星图模拟. 为验证所提方法与现有方法相比的优势, 进行了大量的仿真实验. 实验结果表明, 与现有星图模拟方法相比, 本文方法在保证星图模拟精度的条件下, 选星速度提高了3倍以上.      

超声F扫描检测碳/环氧复合材料层合板冲击损伤—电阻变化

利用超声F扫描方法检测了经不同能量冲击后的碳/环氧复合材料层合板,并测量了复合材料冲击前后电阻.结合冲击能量、电阻变化、超声F扫描图像综合分析了冲击后碳/环氧复合材料的状况.结果表明,超声F扫描能够确定碳/环氧复合材料冲击损伤能量阈值;不同能量的冲击都会使碳/环氧复合材料的电阻发生变化,但只有大于能量阈值的冲击才会在复合材料中产生损伤;超声F扫描提高了基于电阻变化判断复合材料是否损伤的准确性.     

铷吸收半导体激光稳频光波长标准研究

介绍了用铷吸收光谱法对半导体激光器进行稳频,通过对包括半导体激光驱动源、稳频器、吸收室、光路等系统的优化设计,达到具有高信噪比微分误差信号,从而大大提高了半导体激光器稳频锁定灵敏度和长期稳定性。采用文中介绍的方法建立的光波长标准系统,其波长的测量重复性、稳定性可满足当前和将来很长一段时间光波长计校准的需要。     

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。