上海交通大学学报

上海交通大学学报（自然版） ›› 2015, Vol. 49 ›› Issue (06): 751-756.

• 自动化技术、计算机技术 • 上一篇    下一篇

基于EEMD和SVM的冷轧机垂直振动相关故障的诊断

杨旭1，彭开香1，罗浩2，KRUEGER Minjia2 ，宗大桥1，DING Steven X2   

  1. （1.北京科技大学 自动化学院, 北京 100083； 2.Institute for Automatic Control and Complex Systems, University of DuisburgEssen, Duisburg 47057, Germany）
  • 收稿日期:2015-03-11 出版日期:2015-06-29 发布日期:2015-06-29
  • 基金资助:

    国家自然科学基金项目(51205018,61473033)，中央高校基本科研业务费专项资金(FRFTP14121A2)资助

Vibration-Related Fault Diagnosis in Cold Rolling Mill by Using EEMD and SVM

YANG Xu1,PENG Kaixiang1,LUO Hao2,KRUEGER Minjia2,ZONG Dazi1,DING Steven X2   

  1. (1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China; 2. Institute for Automatic Control and Complex Systems, University of DuisburgEssen, Duisburg 47057, Germany)
  • Received:2015-03-11 Online:2015-06-29 Published:2015-06-29

摘要：

摘要：  通过对冷板带轧机垂直振动过程的机理进行分析，结合轧机系统结构模型，建立含振动因素的冷轧机垂向系统动态轧制力模型.考虑复杂工况下，轧机在生产不同规格带钢时，由工艺参数波动等广义故障所致轧机垂直振动现象，基于工业现场数据进行数据驱动的故障诊断算法研究.采用集成经验模态分解算法对实测轧制力信号进行分解，选取有效的固有模态函数的能量作为特征向量，并将其输入到支持向量机分类器中，通过分类器对正常状态和故障状态进行区分，以实现轧机振动相关故障的准确诊断.

关键词: 轧机, 垂直振动, 故障诊断, 支持向量机, 信号处理

Abstract:

Abstract： By analyzing the vibration process of cold rolling and using the structure model of the rolling system, a dynamic rolling force of the rolling vertical system was built, with the consideration of the influence of rolling vibration. A data-driven fault diagnosis was proposed based on industrial field data by using ensemble empirical mode decomposition (EEMD) and support vector machine (SVM), with the focus on the generalized fault, which were mostly caused by variations of process parameters under complex working conditions. According to the decoupling effect on measured rolling force data with the EEMD algorithm, the intrinsic mode function (IMF) component was defined as fault eigenvector and chosen as the input into the classifier of vector machine. Then, the vibration-related fault of cold rolling mills could be diagnosed by  the distinction between the normal state and the fault state by SVM.

Key words: rolling mill, vertical vibration, fault diagnosis, support vector machine(SVM), signal , processing

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