一种基于机器视觉的铅酸蓄电池尺寸检测方法

国内废旧铅酸电池回收效率较低,仍停留在人工分拣与回收处理阶段。为此,提出一种基于机器视觉的智能拆解方法。通过工业相机采集铅酸电池图像后,通过去噪、二值化、连通域提取、边缘检测与作边缘最小外接矩形完成尺寸检测,通过HSV色彩分割、Blob连通域检测完成槽数检测,依据所得的相关检测信息控制切割机对废旧铅酸电池进行切割与回收,实现了高速、高精度检测,提高了电池的回收率及回收效率,减少了对环境造成的污染。

A Method of Size Detection for Lead acid Battery Based on Machine Vision

The recycling efficiency of waste lead acid batteries in China is low and still remains in manual sorting and recycling treatment. Therefore, an intelligent disassembly method based on machine vision was proposed. After the images of lead acid battery was collected by industrial camera, the size detection was completed through denoising, binarization, connected domain extraction, edge detection and making the minimum peripheral rectangle of the edge image; through HSV color segmentation and Blob connected domain detection, the number of slots was detected; the relevant detection information obtained was used to control the cutting machines to cut and recycle waste lead acid batteries. Through this method, high speed and high precision detection are realized, the recovery rate and efficiency of the battery are improved, and the pollution to the environment is reduced.