基于X光图像的锂电池正负极距离检测

Detection of Distance Between Positive and Negative Poles of Lithium Batteries Based on X-Ray Images

针对锂电池正负极缺陷造成严重安全事故的问题,提出一种锂电池正负极距离缺陷检测方法。先获取锂电池的X光图像,通过分水岭算法截取图像中的感兴趣区域,并对感兴趣区域进行旋转校正。针对锂电池负极直线区域难以分割的问题,设计水平方向梯度模板提取正极边界,截取锂电池负极直线部分。利用多尺度视网膜增强算法和扩大差分模板提取负极直线。对提取出的负极直线进行水平投影以获取直线纵坐标,根据正极梯度和提取的负极直线获取正负极端点坐标,进而获取锂电池正负极距离。实验结果表明,所提算法的漏检率低,运行稳定,满足工业要求。

Aiming at the serious safety accidents caused by the defects of positive and negative electrodes of lithium batteries, a defect detection method for the distance between positive and negative electrodes of lithium batteries is proposed. Firstly, the X-ray image of the lithium battery is obtained, the region of interest in the image is intercepted by the watershed algorithm, and the region of interest is rotated and corrected. Secondly, aiming at the problem that it is difficult to segment the negative linear region of the lithium battery, a horizontal gradient template is designed to extract the positive boundary and intercept the negative linear region of the lithium battery. Then, a multi-scale retinal enhancement algorithm and an extended differential template are used to extract the negative line. Finally, the vertical coordinates of the line are obtained by horizontal projection of the extracted negative line, and the coordinates of the positive and negative pole points are obtained according to the positive gradient and the extracted negative line, so as to obtain the positive and negative distances of the lithium battery. The experimental results show that the proposed algorithm has low missing rate and stable operation and meets the industrial requirements.