Detection of micro solder balls using active thermography and probabilistic neural network

Micro solder ball/bump has been widely used in electronic packaging. It has been challenging to inspect these structures as the solder balls/bumps are often embedded between the component and substrates, especially in flip-chip packaging. In this paper, a detection method for micro solder ball/bump based on the active thermography and the probabilistic neural network is investigated. A VH680 infrared imager is used to capture the thermal image of the test vehicle, SFA10 packages. The temperature curves are processed using moving average technique to remove the peak noise. And the principal component analysis (PCA) is adopted to reconstruct the thermal images. The missed solder balls can be recognized explicitly in the second principal component image. Probabilistic neural network (PNN) is then established to identify the defective bump intelligently. The hot spots corresponding to the solder balls are segmented from the PCA reconstructed image, and statistic parameters are calculated. To characterize the thermal properties of solder bump quantitatively, three representative features are selected and used as the input vector in PNN clustering. The results show that the actual outputs and the expected outputs are consistent in identification of the missed solder balls, and all the bumps were recognized accurately, which demonstrates the viability of the PNN in effective defect inspection in high-density microelectronic packaging.     

微分Haar-Gaussian小波变换在大景深物体边缘测量中的应用

提出了微分Haar_Gaussian小波变换算法并将其应用于边缘检测,在空域和频域中进行变换,并应用带宽匹配方法和远心测量光学系统,提高了运算速度,通过对实际大景深物体离焦像的边缘测量,得到了准确的结果。     

基于Radon变换的横向剪切干涉图的自动检测技术

在分析测试原理的基础上,指出了现有方法的横向剪切量获得的不足,根据剪切图和Radon变换在边缘处具有突变的特点,提出了一种基于Radon变换的横向剪切干涉图的剪切量的自动检测方法,首先根据二维图像的Radon变换结果,得到剪切图的横向移动方向,对图形进行方向校正。然后利用干涉图形的特点对图形在X和Y方向上进行Radon变换,得到剪切量。利用MATLAB进行编程,实验结果表明该方法具有很好的性能和较高的实用价值。     

机车轮对轴颈高精度动态检测技术的研究

通过对线阵CCD成像系统的研究,提出了机车轮对轴颈磨损的CCD成像拼接动态检测方法,分析了该方法的可行性.讨论了斜光束照射、背景光强变化等因素,这些因素降低了系统的测量精度.最后通过实验系统证明了该方法的可靠性.     

反恐怖安全检测技术的物理基础

反恐怖安全检测技术已成为人们的热门话题。安全检测技术的诞生和发展离不开物理学家的贡献。物理学为反恐怖安全检测孕育了多种手段和方法。文章简要介绍了X射线探测、γ射线探测、四极共振分析、脉冲式快中子分析、离子迁移率光谱测量、毫米波探测、声学探测、磁场探测、电磁脉冲探测等安全检测技术的物理基础。     

ICF靶丸装配误差检测

针对激光惯性约束聚变装置中靶丸装配误差检测困难、要求精度高的特点,研制了一套用于微靶装配参数检测的测量系统。提出了一种基于激光与CCD的复合式测量方法,建立了二者数据融合的数学模型,通过标定空间位置关系有效地把二者的测量数据融合到同一个坐标系中,从而实现了高精度三维测量。分两种情况讨论了靶丸装配误差的检测方法。实验结果验证了这两种方法的可行性,并比较了两种方法的测量精度,其极限测量误差均不超过3 m。     

一种新型二维X射线探测器

本文建立一种新型X射线探测器,它是一种矩阵寻址方式的二维探测器,由两块玻璃基板组成,分别称作阴极板和阳极板,阴极板内侧镀有行电极和X射线阴级（例如CsI),阳极板上有寻址电极,障壁,两块基板对位封接,使行电要与寻址电极互相垂直,封接后先抽高真空,然后充入氩气与CO2混合气体,本探测器具有薄,轻,图象无畸变并可以利用PDP显示器件的工艺制作大尺寸器件及大量制造等优点。     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.     

快速制取人体组织病理切片的超声波法

本文介绍了用超声波方法快速制妈人体组织病理切片的基本原理，实验步骤和试验结果。结果表明，用超声波处理后快速制取的病理切片完全怀可常规石蜡切片相媲美，在临床外检快速病理诊断应用上，超声处理仪有可能取代价格昂贵的恒温式冷冻切片机。     

服务于智能制造的智能检测技术探索与应用

为了促进工业4.0与“中国制造2025”战略在制造行业的实施,在智能制造体系中构建有效的控制层级与设备层级,促进车间状态数据与智能制造工艺流程的结合,本文提出了通过智能仪器与智能检测技术实现车间状态智能感知与工艺流程控制的方法,并探讨了智能仪器与智能检测技术在智能制造系统中新的应用模式,同时结合实际项目进行了数字化生产线改造与建设的创新实践,提出了满足智能制造要求的智能仪器与检测技术的发展方向。经项目实践验证,通过智能检测设备与智能仪器的应用,可有效促进智能制造系统中数据采集、智能感知的实现,并为整体工艺流程的智能决策提供有效的数据资源,是智能制造系统建立与完善的关键基础。