锂电池极片涂布缺陷明暗场扫描成像检测技术

Defect Inspection of Lithium Battery Electrode Coating via Bright and Dark Field Scanning Imaging Techniques

提出了一种使用多线阵相机、双光源频闪照明成像和分布式并行图像处理技术的锂电池极片涂布涂层缺陷检测方法。该方法使用明、暗光源频闪交替照明,两台高速线扫相机在同一个位置交替分别拍摄明场和暗场图像,既提高了对缺陷的检测分辨能力,也提高了检测效率。在处理环节,该方法使用主从分布式处理架构,使用两台子处理工控机多线程并行处理各自相机的图像数据,并将获得的缺陷数据通过TCP/IP传输至上位处理工控机,进行数据融合与缺陷分类处理。实验表明,使用该方法的锂电池极片涂布检测系统可以实现在线检测,具有极高的实用价值。

In this study,a defect detection approach for lithium battery electrode coating is proposed,which employs an imaging approach with multiple linearray cameras and double light source stroboscopic illumination,and distributed parallel image processing techniques.Especially,bright and dark light sources are employed for stroboscopic illumination in this approach,and two highspeed line scan cameras take the bright and dark field images alternately at the same position,which enhances not only the resolution for defect detection but also the detection efficiency.The masterslave distributed processing architecture is used in the image processing stage.Two industrial control computers process the image data coming from each camera in parallel,and the defect data obtained are sent to the host computer via TCP/IP for data fusion and defect classification.The experimental findings demonstrate that the lithium battery electrode coating detection system using this approach can achieve online detection and has a high practical value.