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Automatic visual inspection system for solder paste deposition in PCBs

机译:PCB中的焊膏沉积自动视觉检查系统

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摘要

The growth of the electronics industry led to a need for efficient methods of testing and validation of printed circuit boards (PCB). It is necessary to identify defects that might appear in a component in early production stages. This task may be performed by automatic inspection systems, showing advantages in speed, accuracy and repeatability, over human inspection. This paper describes a visual inspection system that is able to detect solder paste deposition defects on a PCB. The PCB image is analysed to segment the areas with solder paste and then, by comparing with reference data from the PCB design files, defects are identified, either because of missing or excess solder. The system is based on low cost components, namely a Raspberry Pi Compute Module and two Raspberry Pi v2 cameras. Experimental tests performed with the prototype, regarding the PCB defect detection and execution time, allowed to conclude the system can aid human visual inspection in a production line.
机译:电子行业的增长导致了有效的测试和验证印刷电路板(PCB)的方法。 有必要识别可能在早期生产阶段中的组件中出现的缺陷。 该任务可以通过自动检测系统进行,显示出速度,准确性和可重复性的优势,在人体检查中。 本文介绍了一种可视检测系统,可以检测PCB上的焊膏沉积缺陷。 分析PCB图像以将区域分段为焊膏,然后,通过与来自PCB设计文件的参考数据进行比较,识别缺陷,原因是缺失或多余的焊料。 该系统基于低成本分量,即覆盆子PI计算模块和两个覆盆子PI V2摄像机。 通过原型进行的实验测试,关于PCB缺陷检测和执行时间,允许得出系统可以帮助在生产线中的人体视觉检查。

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