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复杂工业过程质量相关的故障检测与诊断技术综述

彭开香 马亮 张凯

彭开香, 马亮, 张凯. 复杂工业过程质量相关的故障检测与诊断技术综述. 自动化学报, 2017, 43(3): 349-365. doi: 10.16383/j.aas.2017.c160427
引用本文: 彭开香, 马亮, 张凯. 复杂工业过程质量相关的故障检测与诊断技术综述. 自动化学报, 2017, 43(3): 349-365. doi: 10.16383/j.aas.2017.c160427
PENG Kai-Xiang, MA Liang, ZHANG Kai. Review of Quality-related Fault Detection and Diagnosis Techniques for Complex Industrial Processes. ACTA AUTOMATICA SINICA, 2017, 43(3): 349-365. doi: 10.16383/j.aas.2017.c160427
Citation: PENG Kai-Xiang, MA Liang, ZHANG Kai. Review of Quality-related Fault Detection and Diagnosis Techniques for Complex Industrial Processes. ACTA AUTOMATICA SINICA, 2017, 43(3): 349-365. doi: 10.16383/j.aas.2017.c160427

复杂工业过程质量相关的故障检测与诊断技术综述

doi: 10.16383/j.aas.2017.c160427
基金项目: 

国家自然科学基金 61473033

详细信息
    作者简介:

    彭开香北京科技大学自动化学院教授.2007年获得北京科技大学控制科学与工程博士学位.主要研究方向为复杂工业系统故障诊断与容错控制.E-mail:kaixiang@ustb.edu.cn

    张凯北京科技大学自动化学院博士后, 2016年获得德国杜伊斯堡艾森大学博士学位.主要研究方向为数据驱动故障诊断, 统计过程监控, 诊断方法性能评估.E-mail:kai.zhang@uni-due.de

    通讯作者:

    马亮北京科技大学自动化学院博士研究生.2012年获得华北理工大学控制理论与控制工程硕士学位.主要研究方向为数据驱动的故障诊断与容错控制.本文通信作者.E-mail:mlypplover@sina.com

  • 本文责任编委 胡昌华

Review of Quality-related Fault Detection and Diagnosis Techniques for Complex Industrial Processes

Funds: 

National Natural Science Foundation of China 61473033

More Information
    Author Bio:

    Professor at the School of Automation and Electrical Engineering, University of Science and Technology Beijing. He received his Ph. D. degree in control science and engineering from University of Science and Technology Beijing in 2007. His research interest covers fault diagnosis and fault-tolerant control for complex industrial system

    Postdoctor at the School of Automation and Electrical Engineering, University of Science and Technology Beijing. He received his Ph. D. degree from the Institute of Automatic Control and Complex Systems, University of Duisburg-Essen, Germany in 2016. His research interest covers data-based fault diagnosis, statistical process monitoring, and performance assessment for fault diagnosis methods

    Corresponding author: MA LiangPh. D. candidate at the School of Automation and Electrical Engineering, University of Science and Technology Beijing. He received his master degree in control theory and control engineering from North China University of Science and Technology in 2012. His research interest covers data-based fault diagnosis and fault-tolerant control. Corresponding author of this paper
  • 摘要: 质量相关的故障检测与诊断技术是保证安全生产及获得可靠产品质量的有效手段,是当前国际过程控制领域的研究热点.首先,梳理了质量相关的故障检测技术中典型方法的基本思想和改进过程;其次,概述了质量相关的故障诊断技术中常用的贡献图法及其相关改进方法之间的联系,并通过带钢热连轧过程(Hot strip mill process,HSMP)案例比较了各种典型方法在质量相关的故障检测与诊断性能上的异同;最后,面向复杂工业过程运行数据的主要特性,评析了质量相关的故障检测与诊断方法的研究现状,并指出了该研究领域亟需解决的问题和未来的发展方向.
    1)  本文责任编委 胡昌华
  • 图  1  带钢热连轧机布置图

    Fig.  1  Schematic layout of the hot strip mill

    图  2  质量相关的故障检测结果

    Fig.  2  Quality-related fault detection results

    图  3  质量无关的故障检测结果

    Fig.  3  Quality-unrelated fault detection results

    图  4  质量相关的故障诊断结果

    Fig.  4  Quality-related fault diagnosis results

    表  1  对比结果

    Table  1  Comparison results

    方法 计算复杂度 投影结构 子空间个数 统计量个数
    PLS $a$次SVDs 斜交 2 2
    T-PLS $a+3$次SVDs 正交 4 4
    C-PLS $a+2$次SVDs 正交 3 3
    M-PLS 2次SVDs 正交 2 2
    E-PLS 3次SVDs 正交 3 3
    PCR 3次SVDs 正交 3 3
    CVA 1次SVD 正交 2 2
    下载: 导出CSV

    表  2  监测统计量总结

    Table  2  Summary of monitoring statistics

    方法 质量相关故障统计量 质量无关故障统计量
    PLS $T^{2}$ Q
    T-PLS $T_{y}^{2}$和$Q_{r}$ $T_{o}^{2}$和$T_{r}^{2}$
    C-PLS $T_{c}^{2}$ $T_{x}^{2}$和$Q_{x}$
    M-PLS $T_{y}^{2}$ $T_{x}^{2}$
    E-PLS $T_{y}^{2}$ $T_{x}^{2}$和$Q_{x}$
    PCR $T_{y}^{2}$ $T_{o}^{2}$和$Q_{o}$
    CVA $T_{p}^{2}$ $T_{q}^{2}$
    下载: 导出CSV

    表  3  过程及质量变量分配表

    Table  3  Assignment table of process and quality variables

    变量 类型 描述 单位
    1~7 过程变量 第$i$机架的平均辊缝 ($i=1,cdots,7$) mm
    8~14 过程变量 第$i$机架的轧制力 ($i=1,cdots,7$) MN
    15~20 过程变量 第$i$机架的弯辊力 ($i=2,cdots,7$) MN
    21 质量变量 精轧末机架出口厚度 mm
    下载: 导出CSV

    表  4  故障报警率及故障检测率对比结果

    Table  4  FAR and FDR comparison results

    方法 质量相关
    FAR
    质量相关
    FDR
    质量无关
    FAR
    质量无关
    FDR
    PLS 0.1812 0.8680 0.0019 0.9960
    T-PLS 0.2146 0.8920 0.0078 0.9981
    C-PLS 0.2181 0.9713 0.0041 0.9982
    M-PLS 0.1946 0.8480 0.0530 0.9981
    E-PLS 0.2179 0.9712 0.0041 0.9983
    PCR 0.1927 0.9014 0.0052 0.9944
    CVA 0.2011 0.8966 0.0037 0.9929
    下载: 导出CSV
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  • 收稿日期:  2016-06-03
  • 录用日期:  2016-10-14
  • 刊出日期:  2017-03-20

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