基于K-means算法的连铸漏钢预报方法研究  

Study on a breakout prediction method for continuous casting based on the K-Means algorithm

作　　者：师波[1] 代英男 左水利[1] 吴永杰[1] SHI Bo;DAI Ying-nan;ZUO Shui-li;WU Yong-jie(China National Heavy Machinery Research Institute Co.,Ltd.,Xi'an 710032,China;Liaoning Zhongwang Machinery Equipment Manufacturing Co.,Ltd.,Liaoyang 111003,China)

机构地区：[1]中国重型机械研究院股份公司,陕西西安710032 [2]辽宁忠旺机械设备制造有限公司,辽宁辽阳111003

出　　处：《重型机械》2019年第1期38-41,共4页Heavy Machinery

摘　　要：漏钢现象是连铸过程主要操作故障之一,影响连铸生产效率及其设备寿命,漏钢预报一直是连铸研究领域的热门研究课题。本文针对当前连铸漏钢预报系统误报率高和预报准确率低的问题,提出了一种基于K-means算法连铸漏钢预报方法。分析了漏钢预报系统的架构及其连接方式;采用K-means算法对热电偶采取的结晶器坯壳温度数据进行降噪和聚类处理;对某钢厂板坯220 mm×1600 mm连铸机浇铸过程采集到的数据进行测试,测试结果表明,利用K-means算法对正常浇铸数据、温度上升数据和漏钢时刻数据可以正确区分,从而证明了提出连铸漏钢预报方法的有效性。Breakout is one of the main operational failures in the continuous casting process,it reduces the production efficiency and equipment life.Breakout prediction has always been a hot research issue in the field of continuous casting.This paper proposed a breakout prediction method based on the K-means algorithm,it could solve the problem on low prediction accuracy of current breakout prediction system.Firstly,the structure and the connection method of the breakout prediction system are analyzed.Secondly,making noise reduction and clustering on the temperature data of continuous casting mold using the K-means algorithm.Finally,the proposed method was tested using the data of a steel plant,the results show that the K-means algorithm can correctly distinguish the normal casting data,temperature data and breakout data,which proves the effectiveness of the proposed breakout prediction method.

关 键 词：连铸 漏钢预报 数据聚类 K-MEANS算法 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]