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基于极点配置和椭球分析的传感器故障检测

张文瀚 王振华 沈毅

张文瀚, 王振华, 沈毅. 基于极点配置和椭球分析的传感器故障检测. 自动化学报, 2020, 45(x): 1−14 doi: 10.16383/j.aas.c200189
引用本文: 张文瀚, 王振华, 沈毅. 基于极点配置和椭球分析的传感器故障检测. 自动化学报, 2020, 45(x): 1−14 doi: 10.16383/j.aas.c200189
Zhang Wen-Han, Wang Zhen-Hua, Shen Yi. Sensor fault detection based on pole assignment and ellipsoidal analysis. Acta Automatica Sinica, 2020, 45(x): 1−14 doi: 10.16383/j.aas.c200189
Citation: Zhang Wen-Han, Wang Zhen-Hua, Shen Yi. Sensor fault detection based on pole assignment and ellipsoidal analysis. Acta Automatica Sinica, 2020, 45(x): 1−14 doi: 10.16383/j.aas.c200189

基于极点配置和椭球分析的传感器故障检测

doi: 10.16383/j.aas.c200189
基金项目: 国家自然科学基金(61773145, 61973098, 61703296), 哈尔滨工业大学深空探测着陆与返回技术国防重点学科基金 (HIT.KLOF.2018.073), 深圳市科技计划项目(JCYJ20160429115309834)资助
详细信息
    作者简介:

    张文瀚:哈尔滨工业大学航天学院博士研究生. 主要研究方向为基于集员估计技术的故障诊断和容错控制.E-mail: wenhan.zhang@hit.edu.cn

    王振华:哈尔滨工业大学航天学院副教授. 主要研究方向为故障诊断与容错控制技术. 本文通信作者.E-mail: zhenhua.wang@hit.edu.cn

    沈毅:哈尔滨工业大学航天学院教授. 主要研究方向为智能检测、故障诊断、飞行器控制、超声信号处理.E-mail: shen@hit.edu.cn

    通讯作者:

    王振华 哈尔滨工业大学航天学院副教授. 主要研究方向为故障诊断与容错控制技术. 本文通信作者. E-mail: zhenhua.wang@hit.edu.cn

Sensor Fault Detection based on Pole Assignment and Ellipsoidal Analysis

Funds: National Natural Science Foundation of China (Grant No. 61773145, 61973098, 61703296), the Key Laboratory Opening Funds of Harbin Institute of Technology (Grant No. HIT.KLOF.2018.073), and Shenzhen Science & Technology Program (No. JCYJ20160429115309834)
More Information
    Corresponding author: (WANG Zhen-Hua Associate professor at School of Astronautics, Harbin Institute of Technology. His research interest covers fault diagnosis and fault-tolerant control. Corresponding author of this paper.)
  • 摘要: 本文针对具有未知扰动与测量噪声的线性离散时间系统, 提出了一种传感器故障检测方法. 首先, 将传感器故障视为增广状态, 将原始系统转化为一个等效的新线性动态系统. 然后, 基于鲁棒观测器设计和极点配置方法构造了一个故障检测观测器, 使得生成的残差能够同时满足对扰动与噪声的鲁棒性和对故障的敏感性. 此外, 论文设计了一种基于椭球分析的残差评价方法, 该方法可通过判断残差是否被无故障残差椭球包含来检测故障. 最后, 通过一个二阶RC电路模型的仿真算例验证了所提出方法的有效性与优越性.
  • 图  1  二阶RC电路原理图

    Fig.  1  The schematic diagram of the second-order circuit

    图  2  突变故障检测结果指示值

    Fig.  2  Indication of abrupt fault detection result

    图  3  突变故障的残差${{r}}_k$与残差椭球${\cal{E}}(0,R_k)$ ($k = 95\sim105$)

    Fig.  3  Residual ${{r}}_k$ and residual ellipsoid ${\cal{E}}(0,R_k)$ of abrupt fault ($k = 95\sim105$)

    图  4  时变故障检测结果指示值

    Fig.  4  Indication of time-varying fault detection result

    图  5  时变故障的残差${{r}}_k$与残差椭球${\cal{E}}(0,R_k)$ ($k = 95\sim105$)

    Fig.  5  Residual ${{r}}_k$ and residual ellipsoid ${\cal{E}}(0,R_k)$ of time-varying fault ($k = 95\sim105$)

    图  6  微小突变故障检测指示值对比结果

    Fig.  6  Comparison result of small abrupt fault detection indication values

    图  7  本文方法的残差${{r}}_k$与残差椭球${\cal{E}}(0,R_k)$ ($k = 95\sim105$)

    Fig.  7  Residual ${{r}}_k$ and residual ellipsoid ${\cal{E}}(0,R_k)$ by the proposed approach ($k = 95\sim105$)

    图  8  $H_-/H_{\infty}$方法的残差${{\varrho}}_k$与残差椭球${\cal{E}}(0,H_k)$ ($k = 95\sim105$)

    Fig.  8  Residual ${{\varrho}}_k$ and residual ellipsoid ${\cal{E}}(0,H_k)$ by the $H_-/H_{\infty}$ method ($k = 95\sim105$)

    图  9  $H_-/L_{\infty}$方法的残差${{\varsigma}}_k$与残差椭球${\cal{E}}(0,L_k)$ ($k = 95\sim105$)

    Fig.  9  Residual ${{\varsigma}}_k$ and residual ellipsoid ${\cal{E}}(0,L_k)$ by the $H_-/L_{\infty}$ method ($k = 95\sim105$)

    图  10  文献[29]中方法的残差${{\phi}}_k$与无故障残差区间$[\underline{{{\phi}}}_k,\overline{{{\phi}}}_k]$

    Fig.  10  Residual ${{\phi}}_k$ and fault-free residual interval $[\underline{{{\phi}}}_k,\overline{{{\phi}}}_k]$ by the method in [29]

    图  11  本文方法与文献[29]方法的故障检测结果

    Fig.  11  Fault detection results of the proposed method and the approach in [29]

    图  12  本文方法与文献[41]方法的故障检测结果

    Fig.  12  Fault detection results of the proposed method and the approach in [41]

    表  1  本文设计方法与文献[41]中方法的运行时间

    Table  1  Running time of the proposed approach and the method in [41]

    序号 本文方法(s) 文献[41]方法(s)
    1 0.026009 79.884669
    2 0.032881 81.198422
    3 0.029265 82.184995
    4 0.027807 80.956326
    5 0.034486 82.152468
    6 0.030788 81.521354
    7 0.034913 81.125495
    下载: 导出CSV
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