热电池内部缺陷图像识别方法研究  

Recognition algorithm of internal defect images of thermal battery

作　　者：周围[1] 汪芮 孟凡钦 鞠国铭 孟庆宜[2] 张旭 ZHOU Wei;WANG Rui;MENG Fanqin;JU Guoming;MENG Qingyi;ZHANG Xu(School of Mechanical Engineering,Hebei University of Technology,Tianjin 300130,China;School of Energy Engineering,Tianjin Sino-German University of Applied Sciences,Tianjin 300350,China;School of Mechanical Engineering,Tianjin University of Technology and Education,Tianjin 300222,China)

机构地区：[1]河北工业大学机械工程学院,天津300130 [2]天津中德应用技术大学能源工程学院,天津300350 [3]天津职业技术师范大学机械工程学院,天津300222

出　　处：《应用光学》2022年第1期60-66,共7页Journal of Applied Optics

基　　金：“十三五”装备预研共用技术资助项目(41421070102);天津市科技计划项目(20YDTPJC01630);天津职业技术师范大学重点人才启动预研项目(KYQD1815)。

摘　　要：针对目前热电池内部装配缺陷检测效率低、准确度不高的问题,研究了一种可精准分割内部电池堆图像并能够准确识别缺陷种类的方法。首先采用水平、垂直积分投影法对目标电池堆边缘特征进行提取,利用局部自适应对比度增强算法对局部不清晰部分进行细节纹理增强;然后研究了缺陷结构的灰度特性,计算提取出缺陷特征参数;最后使用BP(back propagation)神经网络和CART(classification and regression tree)决策树对特征参数分类识别,并根据分类准确度进行权重分配,将加权融合后的结果作为检测的最终判据。实验结果表明:该方法对2000个样本的检测准确度达98.9%,为热电池的X射线缺陷检测提供了有效的途径。Aiming at the problems of low efficiency and low accuracy in the detection of internal assembly defects of thermal batteries,a method which could accurately segment the internal battery stack images and accurately identify the types of defects was studied.Firstly,the horizontal and vertical integral projection methods were used to extract the edge features of the target battery stack,and the local adaptive contrast enhancement algorithm was used to enhance the detail texture of the local unclear parts.Then,the gray characteristics of the defect structure were studied and the defect characteristic parameters were calculated and extracted.Finally,the BP neural network and CART decision tree were used to classify and identify the feature parameters,the weight was allocated according to the classification accuracy,and the weighted fusion results were used as the final criterion of the detection.The experimental results show that the accuracy of this method is 98.9%for 2000 samples,which provides an effective way for X-ray defects detection of thermal batteries.

关 键 词：热电池 图像分析 缺陷检测 积分投影 

分 类 号：TN206[电子电信—物理电子学] TP391[自动化与计算机技术—计算机应用技术]