赵 涛,张思祥,徐文超,王 哲,赵子豪,周 围.热电池装配缺陷的灰度峰值坐标比对算法[J].电子测量与仪器学报,2020,34(7):133-140
热电池装配缺陷的灰度峰值坐标比对算法
Research on defects detecting method in thermal battery based on a comparison with coordinates of the peaks in gray histogram
  
DOI:
中文关键词:  热电池  模板匹配  峰值坐标  无损检测
英文关键词:thermal battery  template matching  coordinates of the peaks  nondestructive testing
基金项目:“十三五”装备预研共用技术(41421070102)资助项目
作者单位
赵 涛 1. 河北工业大学 机械工程学院,2. 天津理工大学中环信息学院 机械工程系 
张思祥 1. 河北工业大学 机械工程学院 
徐文超 1. 河北工业大学 机械工程学院 
王 哲 1. 河北工业大学 机械工程学院 
赵子豪 1. 河北工业大学 机械工程学院 
周 围 1. 河北工业大学 机械工程学院 
AuthorInstitution
Zhao Tao 1. College of Mechanical Engineering, Hebei University of Technology,2. Department of Mechanical Engineering, Zhonghuan Information College, Tianjin University of Technology 
Zhang Sixiang 1. College of Mechanical Engineering, Hebei University of Technology 
Xu Wenchao 1. College of Mechanical Engineering, Hebei University of Technology 
Wang Zhe 1. College of Mechanical Engineering, Hebei University of Technology 
Zhao Zihao 1. College of Mechanical Engineering, Hebei University of Technology 
Zhou Wei 1. College of Mechanical Engineering, Hebei University of Technology 
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中文摘要:
      针对热电池常见的装配缺陷,提出一种基于热电池电堆区域灰度峰值坐标比对的缺陷检测算法。 通过模板匹配、仿射 变换、灰度矫正、图像放大等预处理算法提取热电池电堆,分析热电池个数错误、漏装负极、漏装集流片、负极与集流片次序放 反、整体倒装 5 种缺陷时,灰度直方图波峰波谷个数、波峰波谷坐标距离等特征与标准电池的区别。 使用该算法对 400 个检测 样本进行实验验证,检测结果正确率达到 95. 5%,结果表明,该算法在热电池的批量无损检测中有较高的实用价值。
英文摘要:
      A method based on a comparison with the coordinates of the peaks in gray scale was proposed to detect the assembly defects of thermal battery. The stack of thermal battery was extracted by template matching. Then image preprocessing methods such as affine transformation, gamma correction and image pyramid were used to improve the contrast of the gray scale. Five defects included the deficiency of monomer thermal battery, the missing of negative electrode, the missing of current collector, wrong assembly order and the overall flip-chip of thermal battery were analyzed. Characteristics in defective battery such as the number of peaks and valleys in gray histogram, distances between the peak and valley were compared with corresponding ones in standard battery. Verified by 400 test images, the experimental results showed that the proposed method possesses an accuracy of 95. 5% and proved that this method can quickly and efficiently detect the defects in thermal battery.
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