SMT焊膏印刷质量AOI技术的研究

本文主要介绍了在微电子表面组装技术(SMT)中,对焊膏印刷质量进行检测的自动光学检测技术(AOI)及其系统的基本概况,讨论了无铅化对焊膏印刷AOI的影响,并对SMT焊膏印刷质量的AOI检测技术的发展趋势进行了分析.     

自动光学检测在中国的应用现状和发展

本文首先概括了自动光学检测(AOI)的测试优点,然后结合具体产品讨论了AOI(包括AXI)的最新技术和发展,以及图像处理算法应用概况。接着对国外几家著名公司AOI产品作了简单介绍,并对国内目前AOI产品的研制情况进行了综述。最后介绍了几种基于AOI的电子组装综合检测技术。     

基于ACR9000控制器的自动光学检测平台设计 

针对自动光学检测(AOI)平台运行过程中的定位精度控制问题,提出了一种基于速度和加速度前馈控制与PID反馈控制的复合控制算法,该算法对输入量进行跟踪补偿控制以消除系统稳态误差,用于提高AOI平台定位精度;基于开放式的数控系统设计方法设计了AOI平台;在Matlab/Simulink环境下,构建了基于该复合控制算法的定位精度控制仿真模型,仿真结果验证了复合控制算法的有效性;将该复合控制算法作为ACR9000控制器的控制算法,并基于ACR9000控制器进行AOI平台实验研究;应用该AOI平台进行了印刷电路板(PCB)检测实验,实验结果表明文中复合控制算法能够提高AOI平台定位精度,AOI平台的定位精度满足印刷电路板检测要求,可以将该AOI平台用于印刷电路板检测。     

AOI技术在PCB缺陷检测中的设计与实现

随着计算机技术和数字图像处理技术的快速发展,传统PCB缺陷检测技术因技术落后已经无法满足现代PCB质量的要求,而AOI技术以其准确、高效的特点在PCB缺陷检测中的应用越来越受到重视.主要研究了AOI技术在PCB缺陷检测中的实际应用,分别进行了硬件选择和软件系统研究,建立了基于AOI技术的PCB缺陷检测系统,采用基于轮廓对比的数据处理方法进行缺陷检测.实验证明了该系统的可行性与实用性.     

提高检测效率导向下自动化测试技术在电子元器件测试中的应用

随着电子制造业的快速发展,电子产品的更新速度越来越快,电子元器件的检测难度日益增大。AOI技术作为一种自动化测试技术不仅满足了快速交付和持续集成的需求,还能够提高检测效率。为研究自动化测试技术在电子元器件测试中的应用,本文以AOI技术检测PCB缺陷为例,进行了基于AOI技术的PCB缺陷检测系统设计,从图像采集、图像预处理、图像定位以及识别缺陷等方面详细介绍了自动化检测技术在电子元器件测试中的应用,证明了自动化检测技术对提高电子元器件的检测效率具有重要的现实意义,以期促进电子制造业的发展。     

国内首台自动光学检测设备研制成功

日前,由中国电子科技集团第45所承担的国际科技合作项目“自动光学检测（AOI）设备技术合作”,通过了国家级验收,技术指标达到了国外同类设备水平,标志着自动光学检测（AOI）设备实现了国产化,填补了国内空白。     

新型高密度电路板的自动光学检测系统设计

为提高自动光学检测系统(AOI)的缺陷检出率,研究了一种采用多色光源照明,利用机器视觉获取被测高密度印刷电路板(HDI型PCB)图像,通过图像处理快速准确地识别出各种缺陷的新型AOI。实验装置由主控计算机、电气控制系统、精密机械运动装置、多色光源照明和图像采集系统等组成。图像处理及识别软件基于OPENCV和VisualStudio2005开发,模块化设计,包括光源控制、图像采集、图像拼接、图像定位、路径规划、缺陷检测和缺陷统计等模块。实验结果表明,新型AOI系统可检出加载HDI型PCB的各种缺陷,缺陷的检出率可达99.9%,误报率只有0.3%。     

ESP8266的无线光色电测试系统设计

ESP8266是一款高性能无线芯片,在家居自动化 、可穿戴设备 、工业无线控制等领域都有广泛的应用.本系统以TFT触摸屏作为用户显示界面,检测命令和检测数据在TFT触摸屏进行显示,以Arduino Leonardo平台作为主控模块,ESP8266作为与功率计和光谱仪的无线通信接口,通过ESP8266进行命令和数据的透传,解决了检测设备的无线通信问题.     

泓格无风扇嵌入式影像检测平台Vision Box VB-115／VB-216系列

泓格科技最新发表的Vision Box系列是一个完全无风扇的平台设计．适合搭配MAVIS IEEE 1394工业级摄影机应用在AOI光学检测系统上。     

基于Freescale微控制器的AOI多彩照明控制系统

为了检测出高密度印刷电路板(HDI PCB)中的多种焊接缺陷,对用于自动光学检测(AOI)设备的多角度多色彩LED照明装置的控制系统进行软硬件改进,设计了一种以Freescale--MC9H12XS128为微控制器的多彩照明控制系统。控制系统的硬件结构简单,可同时对4组LED阵列进行脉宽调制控制,根据实际图像的提取效果,通过接收主控上位机发出的指令,对不同LED阵列进行颜色选择和256级光照亮度的调节。实验结果表明,该系统能满足AOI设备对照明装置提出的各种要求,使照明系统光照均匀,光强可调,响应快,发热量小。     

Artificial intelligence-assisted auto-optical inspection toward the stain detection of an organic light-emitting diode panel at the backplane fabrication step

This paper attempts to implement an auto-optical inspection (AOI) system using artificial intelligence (AI) technology for cost reduction in the production of organic light emitting diode (OLED) panels, specifically at the production stage of the thin film transistor (TFT) . Further, to improve the accuracy of mura detection, the possible causes of mura were properly identified, and a model to control and predict mura occurrence was realized based on the sufficient analysis of these causes. More specifically, an explainable AI (XAI) prediction model was developed using the fab image and test element group (TEG) engineering methods, which could be applied as input data for the circuit simulations to improve the accuracy of the overall simulations. Initially, we attempted to predict backplane stain using only the TFT width, length dimension, and resistance–capacitance (RC) extraction data, but the results were not accurate. Consequently, we identified, via sufficient analysis, that the correlation between the dehydrogenation and stain, and introduced an AI model. As a result, the accuracy was improved from 50 to 80%, which is more effective in terms of time and cost, compared to conventional simulation through the TCAD analysis. Overall, by implementing the inspection method described in this paper, it was possible to detect stains at the backplane stage, which was only possible during the final test stage, thereby resulting in significant cost savings.     

Critical point defect detection for small‐pixel thin‐film transistor array applied to medical display

Thin‐film transistor (TFT) array testing technique has been used, which provides defect detection capability to control the yield of the TFT process. In the past, several defect inspection technologies have been developed and applied for the TFT array testing. When the TFT array pixel size is getting smaller and the resolution is higher, they also encounter the performance limitation on detecting the critical defect in this small‐pixel TFT array and facing a limited testing requirement. For medical display applications, the display pixels on an array panel are getting smaller and smaller; therefore, defect detection is getting more important and critical for managing yield with quality. In this study, a novel approach for defect detection was proposed. Here, the proposed voltage imaging technique is used for the TFT array test, and it provides better small‐pixel TFT array defect detection capability. The experimental results show that by using the voltage imaging technique, detecting critical point defect of TFT array can be effectively improved. And the detected small‐pixel size of TFT array panels can be smaller than 55 µm of an advanced medical display.     

基于注意机制的实时红外舰船检测

为了提高红外舰船图象检测的实时性 ,提出了一种基于多分辨率注意机制的红外舰船图象检测方法 ,该方法是利用注意机制来降低待处理数据量 ,并将注意过程分为“预注意”和“注意”两个阶段 ,同时采用非线性采样模型 ,在降低预注意分辨率的同时 ,使该方法能适应目标大小变化 ;检测时 ,将红外舰船图象中舰船发动机或烟囱所在的热区域作为“预注意”的特征 ,先将注意引导到感兴趣区域上 ,再在感兴趣区域内检测吃水线特征 .实验证明 ,该方法能有效地提高红外舰船检测的效率 ,并对目标大小变化有一定的适应能力 .     

An in‐cell capacitive touch sensor integrated in an LTPS WSVGA TFT‐LCD

This paper discusses an In‐cell capacitive touch sensor and its integration in an LTPS TFT‐LCD with 7‐inch screen size and WSVGA resolution. The operation of the newly developed sensor is based on capacitive coupling between user's finger and the detection electrode on the TFT substrate, and is purely capacitive. The sensors and the sensor driver circuits have been integrated in the TFT substrate of the prototype TFT‐LCD using LTPS technology. The prototype having 256x150 sensors shows advantages such as smooth operation with no touch force, high position accuracy, multi‐touch (10 or more), a thin and light LCD module, high display quality, and thus is suitable for various applications such as cell‐phones, smart‐phones, mobile‐PCs, and automotive‐use displays.     

液晶显示屏背光源模组表面缺陷自动光学检测系统设计

详细介绍了自动光学检测技术在液晶显示屏背光源模组表面缺陷在线检测中的应用,分析并比较了背光源模组缺陷自动光学在线检测中的成像技术、检测系统的组成、结构原理与设计方法,阐述了检测结果为不良品的返修方法。给出了背光源模组表面缺陷常见缺陷的种类和缺陷分类判断准则,把种类繁多的背光源模组表面缺陷分为画面缺陷、外观缺陷与异常缺陷;根据背光源模组缺陷形成的原因、种类,设计了背光源模组缺陷点灯检测和非点灯检测两种自动光学检测方案,所设计的自动光学检测方案对背光源模组组装产业开发缺陷检测系统具有有益的参考价值。     

IGZO‐TFT technology for large‐screen 8K display

We succeeded in G8 factory for mass production of Indium–Gallium–Zink–Oxide thin‐film transistor (IGZO‐TFT) for the first time in the world. The initial TFT process was an etching stop‐type TFT, but now, we are mass producing channel etching‐type TFTs. And, its application range is smartphones, tablets, PCs, monitors, TV, and so on. In particular, because of recent demands for high‐resolution and narrow frame, our IGZO display has been advanced in technology development with gate driver in panel. In this paper, we report development combining low resistance technology and the latest IGZO‐TFT (IGZO5) for large‐screen 8K display.     

基于PicoBlaze软核的TFT液晶显示控制

介绍基于8位嵌入式软核PicoBlaze的SOPC的设计方法,提出一种基于PicoBlaze软核的TFT液晶显示控制方案,并给出了软硬件设计方法.实验结果表明,该方案占用资源少,运行速度快,可以为FPGA驱动TFT液晶提供设计参考.     

Novel LTPS technology for large substrate

We developed partial laser anneal silicon (PLAS) thin‐film transistor (TFT) of novel low‐temperature polycrystalline‐silicon (LTPS) technology, which had the mobility of 28.1 cm²/Vs lager than that of mass produced oxide TFT and photo‐stability comparable with that of LTPS TFT in bottom gate structure. This innovative technology enables the conversion from an α‐Si TFT to a high‐mobility TFT most easily and inexpensively. Moreover, there is no limit of substrate size, such as Gen10 and more. Photo‐stability of PLAS will be suitable to organic light‐emitting diode backplane, high‐dynamic range TV, and outdoor IDP.     

基于机器视觉的高密度电路板缺陷检测系统

为减少高密度电路板的缺陷误报率,研究一种新型自动光学检测系统(AOI);系统采用自行研制的多色LED照明系统,利用机器视觉获取被测PCB的图像,通过图像处理软件系统快速准确地识别出各种缺陷;系统利用获取的彩色图像信息,根据各种缺陷的特征信息不同,采用OPENCV对各种缺陷的检测算法进行改进,使得系统性能有很大改进;对30块同类HDI型PCB的36300个检测点进行测试,测试结果证明,系统PCB缺陷的检出率高达99.87%,误报率只有0.32%。