局部对比度增强的热电池缺陷检测算法  

Research on defects detecting method in thermal battery based on local contrast enhancement algorithm

作　　者：赵涛 张思祥[1] 王哲[1] 徐文超[1] 肖鑫 汪芮 ZHAO Tao;ZHANG Sixiang;WANG Zhe;XU Wenchao;XIAO Xin;WANG Rui(School of Mechanical Engineering,Hebei University of Technology,Tianjin 300131,China;Department of Mechanical Engineering,Zhonghuan Information College Tianjin University of Technology,Tianjin 300380,China)

机构地区：[1]河北工业大学机械工程学院,天津300131 [2]天津理工大学中环信息学院机械工程系,天津300380

出　　处：《激光杂志》2022年第1期24-28,共5页Laser Journal

基　　金：“十三五”装备预研共用技术(No.41421070102);天津市教委科研计划项目(No.2020KJ077)。

摘　　要：针对射线源管电压限制引起的X射线透射图像局部纹理特征不明显的问题,提出了局部对比度增强的改进灰度峰值坐标比对算法。以某型号热电池为例,通过试验确定了管电压变化对电池堆负极、集流片灰度变化规律的影响,分析了管电压与图像标准差、平均梯度、信息熵之间的关系,确定了缺陷检测的理想管电压值。对于大尺寸热电池,通过自适应对比度增强(ACE)算法提取电池堆波峰波谷信息进行灰度峰值坐标比对,解决了X光线倾斜入射波谷坐标提取的准确性的问题,将漏装集流片缺陷和次序错误缺陷的检测正确率分别提高到了96%和92%。Aimed at the problem of inconspicuous local texture features in X-ray transmission images caused by the voltage limitation of the ray source tube, an improved gray-scale peak coordinate comparison algorithm for local contrast enhancement is proposed. Take thermal battery as an example, the influence of tube voltage change on the gray change law of the negative electrode of the battery stack and the current collector is determined through experiments. The relationship between the changed tube voltage and the image standard deviation, average gradient, and information entropy is researched. Determined the ideal tube voltage. For large size thermal batteries, The peak and valley information of the battery stack is extracted by the adaptive contrast enhancement(ACE) algorithm for gray-scale peak coordinate comparison. The problem of the accuracy of the extraction of X-ray oblique incident valley coordinates is solved. Increased the detection accuracy rates of missing-assembled tape-out defects and sequence-error defects to 96% and 92% respectively.

关 键 词：管电压 热电池 缺陷检测 对比度增强 

分 类 号：TN219[电子电信—物理电子学]