摘要
在钢材冷轧加工领域,精准检测板形缺陷对于保障产品质量与生产稳定性至关重要。为提高钢材冷轧加工过程中的板形加工质量,使板形更为精准,基于工业摄像头和激光器搭建检测方案,从图像处理、边缘检测、关键信息提取等多个环节着手,提出一种基于辅助激光线的板形检测方法,并明确了该方法下的可逆神经网络、Canny边缘检测、基于Steger算法的光条中心提取等算法流程。结果显示,该方法可对钢材冷轧加工过程中常见的板形中间起拱、中部凹陷和单边波浪等问题实现较为精准的检测,表明该方法可保证钢材冷轧质量,降低次品率,为钢铁行业高效生产提供有力的技术支撑。
In the field of steel cold rolling processing,precise detection of plate shape defects is crucial for ensuring product quality and production stability.To improve the plate shape processing quality during steel cold rolling and achieve more accurate plate shapes,a detection scheme is established based on industrial cameras and lasers.Starting from multiple aspects such as image processing,edge detection,and key information extraction,a plate shape detection method based on auxiliary laser lines is proposed,and the algorithmic processes under this method,including reversible neural networks,Canny edge detection,and light stripe center extraction based on the Steger algorithm,are clarified.The results show that this method can achieve relatively accurate detection of common plate shape issues during steel cold rolling,such as middle arching,central sagging,and unilateral waviness.This indicates that the proposed method can ensure the quality of steel cold rolling,reduce the defect rate,and provide strong technical support for efficient production in the steel industry.
作者
郑帅
ZHENG Shuai(Shanxi Xuchuang Safety Technology Service Co.,Ltd.,Taiyuan,Shanxi 030000,China)
出处
《自动化应用》
2025年第15期282-283,287,共3页
Automation Application
关键词
钢材冷轧机
板形检测
检测技术
steel cold rolling mill
plate shape detection
detection technique
