电子测量与仪器学报

吴昆鹏,王孝敏,崔广礼,邓能辉,石杰.粗轧板坯自动转钢系统研究与应用[J].电子测量与仪器学报,2024,38(1):114-123

粗轧板坯自动转钢系统研究与应用

Research and application of automatic steel transfersystem for rough rolling billets

DOI：

英文关键词:rough rolling automatic steel transfer PIDNet angle tracking control strategy

基金项目:

作者	单位
吴昆鹏	北京科技大学国家板带生产先进装备工程技术研究中心北京100083
王孝敏	江阴兴澄特种钢铁有限公司厚板分厂无锡214400
崔广礼	北京科技大学国家板带生产先进装备工程技术研究中心北京100083
邓能辉	北京科技大学国家板带生产先进装备工程技术研究中心北京100083
石杰	北京科技大学国家板带生产先进装备工程技术研究中心北京100083

Author	Institution
Wu Kunpeng	National Engineering Technology Research Center of Flat Rolling Equipment, University of Science and Technology Beijing, Beijing 100083,China
Wang Xiaomin	Jiangyin Xing Cheng Special Steel Co., Ltd. Heavy Plate Branch, Wuxi 214400, China
Cui Guangli	National Engineering Technology Research Center of Flat Rolling Equipment, University of Science and Technology Beijing, Beijing 100083,China
Deng Nenghui	National Engineering Technology Research Center of Flat Rolling Equipment, University of Science and Technology Beijing, Beijing 100083,China
Shi Jie	National Engineering Technology Research Center of Flat Rolling Equipment, University of Science and Technology Beijing, Beijing 100083,China

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中文摘要:

宽厚板生产过程中，其粗轧工艺需控制交叉的锥形辊实现板坯长宽方向的对调，该过程严重依赖人工操作，节奏无法有效控制，制约生产线智能化改造进程。结合视觉检测和自动控制技术设计的粗轧板坯自动转钢系统可有效解决该问题，在粗轧机出入口分别安装视频监控相机，捕捉转钢辊道区域上板坯的状态，利用改进的包含去雾模块的PIDNet（proportional integral derivative network）模型提取板坯前景轮廓，通过组合式角度度量方法实时跟踪板坯旋转角度。过程中融合安全限位、位置优选、速度调控、过转修正等策略共同优化转钢控制，保证转钢的安全稳定，自主学习人工经验提升转钢效率。应用结果表明，系统可准确测量板坯角度并实现自动转钢功能，能够替代人工操作，节省能耗，实现智能化生产的目的。

英文摘要:

In the production process of wide and thick plates, the rough rolling process requires the control of intersecting conical rollers to achieve the adjustment of slab length and width direction. This process heavily relies on manual operation, and the rhythm cannot be effectively controlled, which hinders the intelligent transformation process of the production line. The automatic steel transfer system for rough rolling slab, designed by combining visual inspection and automatic control technology, can effectively solve this problem. Video surveillance cameras are installed at the entrance and exit of the rough rolling mill to capture the status of the slab in the steel transfer roller area. The PIDNet model with an improved defogging module is used to extract the foreground contour of the slab, and the slab rotation angle is tracked in real time through a combination angle measurement method. During the process, strategies such as safety limit, position optimization, speed regulation, and over rotation correction are integrated to jointly optimize the control of the steel conversion process, ensuring the stability and safety of the steel conversion. Autonomous learning of manual experience improves the efficiency of steel conversion. The application results show that the system can accurately measure the angle of the slab and achieve automatic steel conversion function, which can replace manual operation, save energy consumption, and achieve the goal of intelligent production.

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