摘要
Abstract
In the key process of recycling and reusing new energy batteries,the milling process of battery sealing pins is of vital importance.The sealing pins need to be milled and then the electrolyte drained.This process is previously mostly carried out manually,and improper operation could cause sparks from the drill bit to ignite and lead to an explosion,endangering human lives.Moreover,the traditional manual milling method is not only inefficient,but also unable to guarantee precision,and cannot meet the requirements of large-scale recycling.Therefore,through in-depth research on visual recognition technology and system integration,a complete system solution is designed.The system uses a high-resolution camera to obtain the position and posture information of the battery sealing pins,and then uses image processing algorithms for precise recognition and positioning.The data is then transmitted to the motion control system to drive the milling device to complete the precise milling operation.In terms of visual recognition,advanced edge detection algorithms are adopted to improve the recognition accuracy of different types of battery sealing pins,and the visual repetitive positioning accuracy can reach±0.005 mm.The application of this system not only significantly improves the efficiency and quality of milling the sealing pins,but also effectively reduces labor costs and safety risks,and is of great significance for the automation and intelligence development of sealing pin milling.关键词
新能源电池回收/机器视觉/铣钉机/控制系统Key words
new energy battery recycling/machine vision/milling machine/control system分类
信息技术与安全科学
