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期刊信息
  • 主管单位:
  • 中国科学技术协会
  • 主办单位:
  • 中国仪器仪表学会、上海光学仪器研究所、中国光学学会工程光学专业委员会
  • 主  编:
  • 庄松林
  • 地  址:
  • 上海市军工路516号上海理工大学《光学仪器》编辑部
  • 邮政编码:
  • 200093
  • 联系电话:
  • 021-55270110
  • 电子邮件:
  • gxyq@usst.edu.cn
  • 国际标准刊号:
  • 1005-5630
  • 国内统一刊号:
  • 31-1504/TH
  • 邮发代号:
  • 单  价:
  • 15.00
  • 定  价:
  • 90.00
PCB焊点及芯线端头识别
Recognition of PCB solder joints and core wire ends
投稿时间:2022-02-28  
DOI:10.3969/j.issn.1005-5630.2022.005.006
中文关键词:  HSV颜色空间  RGB通道分离  阈值分割  连通域分析  轮廓检测
英文关键词:HSV color space  RGB channel separation  threshold segmentation  connected domain analysis  contour detection
基金项目:国家自然科学基金青年基金 (62005167)
作者单位E-mail
刘翰林 上海理工大学 光电信息与计算机工程学院上海 200093  
张荣福 上海理工大学 光电信息与计算机工程学院上海 200093 zrf@usst.edu.cn 
摘要点击次数: 49
全文下载次数: 40
中文摘要:
      智能微型化的医用器械在医疗行业逐渐被人们所重视。这些产品主要是由一些微型电子元器件构成,其中器件核心芯片部分的点线连接结构需通过高精密焊接工作完成。因此焊点和被焊芯线的识别精度要求越来越高,两者是否能准确有效识别直接影响焊接的最终质量。为高质量完成焊接过程中的焊点和芯线识别,本文主要使用电子显微仪器结合上位机VS17+OpenCV软硬结合的方法完成图像处理,对所采集图像中的焊点和芯线端头进行识别。以焊点和芯线端头的颜色及几何特征作为分析对象,经预处理后再通过各自特征分析突出感兴趣区域部分,通过特定颜色阈值选取方式和对比度提升算法完成焊点和芯线端头的分割过程,要求所测量焊点及芯线端头的识别精度误差≤0.1 mm。实验结果表明:本文印刷电路板(PCB)焊点及芯线端头的识别算法能有效识别焊点及芯线端头图中所在位置并显示其像素坐标值;经数据整理分析,本文算法的识别精度误差均控制在允许的误差范围内。
英文摘要:
      Intelligent miniaturized medical devices have attracted more and more attention in the medical industry. These products are mainly composed of some micro electronic components, in which the point line connection structure of the device core chip needs to be completed by high-precision welding. Therefore, the higher recognition accuracy of solder joint and welded core wire is required. Whether they can be accurate and effective identification directly affects the final quality of welding. In order to complete the recognition of solder joint and core wire in the welding process with high quality, this study mainly uses the method of electronic microscope instrument combined with host computer VS17 + OpenCV to complete the image processing, and recognizes the solder joint and core wire end of the collected image. The color and geometric features of solder joint and core wire end are taken as the analysis object. After preprocessing, the region of interest is highlighted through their respective feature analysis. The segmentation process of solder joint and core wire end is completed through specific color threshold selection method and contrast enhancement algorithm. The recognition accuracy error of measured solder joint and core wire end is required within 0.1 mm. The experimental results show that the proposed identification algorithm of printed circuit board (PCB) solder joint and core wire end can effectively identify the position of solder joint and core wire end in the image and display its pixel coordinate value. After data sorting and analysis, the identification accuracy error of this algorithm is controlled within the tolerable range.
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