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

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97.5%满足检测要求,为热电池缺陷检测提供了有效途径。

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 97.5%and meets the testing requirements,which provides an effective way for thermal battery defect detection.