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基于状态集员估计的主动故障检测

王晶 史雨茹 周萌

王晶, 史雨茹, 周萌. 基于状态集员估计的主动故障检测.自动化学报, 2021, 47(5): 1087-1097 doi: 10.16383/j.aas.c180830
引用本文: 王晶, 史雨茹, 周萌. 基于状态集员估计的主动故障检测.自动化学报, 2021, 47(5): 1087-1097 doi: 10.16383/j.aas.c180830
Wang Jing, Shi Yu-Ru, Zhou Meng. Active fault detection based on state set-membership estimation. Acta Automatica Sinica, 2021, 47(5): 1087-1097 doi: 10.16383/j.aas.c180830
Citation: Wang Jing, Shi Yu-Ru, Zhou Meng. Active fault detection based on state set-membership estimation. Acta Automatica Sinica, 2021, 47(5): 1087-1097 doi: 10.16383/j.aas.c180830

基于状态集员估计的主动故障检测

doi: 10.16383/j.aas.c180830
基金项目: 

国家自然科学基金 61573050

国家自然科学基金 51805021

东北大学流程工业综合自动化国家重点实验室资助开放项目 PAL-N201702

中央高校基本科研专项基金 XK1802-4

中国博士后科学基金 2018M631311

详细信息
    作者简介:

    王晶   北方工业大学电气与控制工程学院教授. 主要研究方向为非线性、多变量、受约束的工业过程的先进控制方法的应用, 复杂的工业过程的建模、优化和控制, 化学反应器中聚合物微观质量的非线性模型控制, 过程监控和复杂工业过程的故障诊断. E-mail: jwang@ncut.edu.cn

    史雨茹   北京化工大学信息科学与技术学院硕士研究生. 主要研究方向为主动故障检测和诊断.E-mail: 2017200743@mail.buct.edu.cn

    通讯作者:

    周萌   北方工业大学电气与控制工程学院副教授. 主要研究方向为故障诊断与容错控制. 本文通信作者. E-mail: zhoumeng@ncut.edu.cn

Active Fault Detection Based on State Set-membership Estimation

Funds: 

National Natural Science Foundation of China 61573050

National Natural Science Foundation of China 51805021

the Open-Project Grant Funded by the State Key Laboratory of Synthetical Automation for Process Industry at Northeastern University PAL-N201702

Fundamental Research Funds for the Central Universities XK1802-4

China Postdoctoral Science Foundation 2018M631311

More Information
    Author Bio:

    WANG Jing  Professor at the School of Electrical and Control Engineering, North China University of Technology. Her research interest covers application of advanced control schemes to nonlinear, multivariable, constrained industrial processes; modeling, optimization and control for complex industrial process; nonlinear model-based control of polymer microscopic quality in chemical reactor; process monitoring and fault diagnosis for complex industrial process

    SHI Yu-Ru    Master student at the College of Information Science and Technology, Beijing University of Chemical Technology. Her research interest covers active fault detection and diagnosis

    Corresponding author: ZHOU Meng   Associate professor at the School of Electrical and Control Engineering, North China University of Technology. Her research interest covers fault diagnosis and fault tolerance control. Corresponding author of this paper
  • 摘要: 对于现代复杂控制系统, 微小故障往往很难发现. 在系统过程干扰和测量噪声未知但有界的前提下, 提出了一种新的基于状态集员估计的主动故障检测方法. 首先设计全对称多胞形卡尔曼滤波器对系统状态进行估计, 并利用全对称多胞形对受未知干扰影响的状态集合进行描述, 然后设计辅助输入信号使得加入辅助输入信号后正常模型的状态集合与故障模型的状态集合交集为空, 从而实现主动故障检测. 为了使得所设计的辅助输入信号对原系统影响最小, 需要求得最小的辅助输入信号, 本文将最优化问题转化为混合整数二次规划问题进行求解. 最后, 与基于输出集合的辅助输入信号设计方法对比, 仿真验证本文所提出的基于状态集合的主动故障检测方法由于未受下一时刻测量噪声的影响, 所求得的辅助输入信号更小, 保守性更低.
    Recommended by Associate Editor XIN Jing-Min
    1)  本文责任编委 辛景民
  • 图  1  在正常模型和故障模型下, 加入辅助信号与未加辅助信号结果的对比

    Fig.  1  Comparison of the results of adding auxiliary signals and unassisted signals under normal and fault models

    图  2  在正常模型和故障模型下, 加入辅助信号对状态和输出的影响

    Fig.  2  The effect of adding an auxiliary signal on state and output under normal and fault models

    图  3  辅助输入信号

    Fig.  3  The auxiliary input signal

    图  4  加入辅助信号和未加辅助信号对系统输出的影响

    Fig.  4  Effect of adding auxiliary signal and unassisted signal on system output

    图  5  状态多胞形: 通过状态交集为空的方法

    Fig.  5  Zonotope of the system state: the method of emptying the state intersection

    图  6  故障检测结果

    Fig.  6  The results of fault detection

    图  7  输出多胞形: 通过输出交集为空的方法

    Fig.  7  Zonotope of the system output: the method of emptying the output intersection

    图  8  状态多胞形: 通过输出交集为空的方法

    Fig.  8  zonotope of the system state: the method of emptying the output intersection

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出版历程
  • 收稿日期:  2018-12-13
  • 录用日期:  2019-04-26
  • 刊出日期:  2021-05-21

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