一种电能表可信生产贴片环节采集验证方法和系统

针对当前电能表电路板中元器件贴片异常现象，基于新型的计算机视觉技术、图像采集技术、识别技术、自动化控制技术，设计出了新型的电能表可信生产贴片环节采集验证方法和系统，对智能电能表PCB贴片信息进行采集、检测和异常判断。本研究将双六轴联动控制系统融入系统设计中，在空间范围内实现不同位置的电能表三维运动，利用CCD相机进行上下运动，在平面、侧面、三维等多角度扫描PCB贴片信息，对光源系统进行RGB三基色谐调智能调节，调整彩色CCD相机参数信息和运动控制系统定位信息，从而获取二元或者灰度水平光学成像图像，并利用标准模板库与电子元器件进行比对，通过大数据算法查询目标数据库，实现PCB贴片信息的判断。实验表明，本研究的算法检测时间快，正确率高，大大提高了生产效率。

Abnormal flow detection of process layer network in Intelligent Substation

Based on the new computer vision technology, image acquisition, identification technology and automatic control technology, a new method and system for collecting and verifying the reliable production patch link of the energy meter has been designed based on the new computer vision technology, image acquisition technology, identification technology and automatic control technology. Collect, detect and abnormally judge the PCB patch information of the intelligent electric energy meter. In this study, the dual six-axis linkage control system is integrated into the system design to realize the three-dimensional movement of the energy meter at different positions in the spatial range. The CCD camera is used to move up and down, and the PCB patch information is scanned at multiple angles on the plane, side, and three dimensions. , Intelligent adjustment of RGB three primary colors in the light source system, adjust the color CCD camera parameter information and motion control system positioning information, so as to obtain binary or gray level optical imaging images, and quickly query the target database through the big data algorithm to realize the judgment of PCB patch information. Experiments show that the algorithm of this study has fast detection time and high accuracy, which greatly improves production efficiency.