基于机器视觉的图像处理技术识别锂电池极片的缺陷

Image Processing Technology based on Machine Vision to Identify Defects of Lithium Battery Electrodes

针对锂电池的正负极极片在生产过程会出现破损、划痕等缺陷,提出了一种基于机器视觉的锂电池极片缺陷检测方法。通过对锂电池极片图像进行去燥、边缘检测、霍夫直线检测等手段准确检测出锂电池极片缺陷的轮廓,基于图像的梯度计算缺陷轮廓面积。实验结果表明,该算法相较于传统的缺陷检测方法,处理速度更快、准确度更高。

Aiming at the defects of the positive and negative pole pieces of lithium batteries in the production process,such as damage,scratches,etc.,a method for detecting lithium battery pole piece defects based on the machine vision is proposed in this paper.The contours of lithium battery pole piece defects could be accurately detected by means of de-drying the lithium battery polar images,edge detection,Hough straight line detection,and so on;and the defect outline area is calculated based on the image gradient.The experimental results show that the algorithm is faster and more accurate than the traditional defect detection methods.