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Intelligence study of control strategy in BGA rework process

机译:BGA返工过程中控制策略的智能研究

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摘要

As one branch of electronic components reuse techniques, research on BGA rework process is significant for ecology and economy. In this paper, one effective control project of heating temperature, reliability detecting of solder joints and automatic adjusting of BGA chip position is proposed, which extremely increases the degree of the artificial intelligence of BGA rework process with using the methods such as Fuzzy-PID theory, Blob analysis algorithm and SIFT feature points extraction and matching algorithm. Put the fuzzy self-tuning PID controller into use in the temperature control system of one electronic assembly equipment, which can achieve the real-time on-line correction of PID parameters and the temperature regulation result that is better than using the conventional PID controller especially in terms of the stability. The information of connected areas in BGA chip image provides basis for automatic reliability detecting of solder joints. SIFT algorithm is able to achieve the match between template image and target image without angle information, so that the precise angle to rotate becomes acquirable.
机译:作为电子元件再利用技术的一个分支,对BGA返工过程的研究对于生态和经济意义重大。本文提出了一种有效的加热温度控制,焊点可靠性检测和BGA芯片位置自动调整的控制方案,通过使用Fuzzy-PID理论等方法极大地提高了BGA返工过程的人工智能程度。 ,斑点分析算法和SIFT特征点提取与匹配算法。一台电子装配设备的温度控制系统中使用了模糊自整定PID控制器,可以实现PID参数的实时在线校正,温度调节效果比传统PID控制器要好。在稳定性方面。 BGA芯片图像中连接区域的信息为自动检测焊点可靠性提供了基础。 SIFT算法能够在没有角度信息的情况下实现模板图像和目标图像之间的匹配,从而获得精确的旋转角度。

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