张思祥,胡雪迎,竭霞,李思鸣,王哲,赵子豪,周围.单体热电池装配缺陷的图像检测方法研究[J].电子测量与仪器学报,2019,33(2):132-139 |
单体热电池装配缺陷的图像检测方法研究 |
Research on image detection method for assembly failure of monomer thermal battery |
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DOI: |
中文关键词: 单体热电池 改进灰度共生矩阵 HU不变矩 模板匹配 CART决策树分类器 |
英文关键词:monomer thermal battery improved gray level co occurrence matrix HU invariant moment template matching classification and regression tree(CART) decision tree |
基金项目:“十三五”装备预研共用技术(41421070102)资助项目 |
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中文摘要: |
针对目前国内外热电池内部装配缺陷检测准确度不高的问题,研究一种基于图像检测热电池内部的单体热电池缺陷的检测方法。其中分析了单体热电池整体倒装、单体热电池装配次序、单体热电池漏装集流片3种常见的缺陷的特征, 利用改进的灰度共生矩阵、HU 不变矩和模板匹配三种算法对单体热电池进行缺陷分析。最后利用分类回归树(CART)进行检测,提出一种按权重分配参数的检测方法,实验结果表明,这种方法准确度达到 975%满足检测要求,为热电池缺陷检测提供了有效途径。 |
英文摘要: |
A method for detecting defects of monomer thermal battery inside the thermal battery is proposed in this paper, which aimed at the problem of the low accuracy of internal assembly fault detection at home and abroad. This detection includes three defects, the overall flip chip of the monomer thermal battery, the assembly sequence of the monomer thermal battery, and the leakage of the monomer thermal battery part are analyzed. Using the improved gray level co occurrence matrix, HU invariant moment, template matching to analyze the defects of monomer thermal batteries. Finally, proposing a detection method based on weight distribution parameters, which is using CART (Classification and Regression Tree) decision tree for detection. The experimental results show that the accuracy of this method reaches 975% and meets the testing requirements, which provides an effective way for thermal battery defect detection. |
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