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基于中心对称多胞体的故障可分离性评价

王桢榕 王振华 沈毅

王桢榕, 王振华, 沈毅. 基于中心对称多胞体的故障可分离性评价. 自动化学报, 2022, 48(8): 1921−1930 doi: 10.16383/j.aas.c190770
引用本文: 王桢榕, 王振华, 沈毅. 基于中心对称多胞体的故障可分离性评价. 自动化学报, 2022, 48(8): 1921−1930 doi: 10.16383/j.aas.c190770
Wang Zhen-Rong, Wang Zhen-Hua, Shen Yi. Fault isolability evaluation based on zonotope. Acta Automatica Sinica, 2022, 48(8): 1921−1930 doi: 10.16383/j.aas.c190770
Citation: Wang Zhen-Rong, Wang Zhen-Hua, Shen Yi. Fault isolability evaluation based on zonotope. Acta Automatica Sinica, 2022, 48(8): 1921−1930 doi: 10.16383/j.aas.c190770

基于中心对称多胞体的故障可分离性评价

doi: 10.16383/j.aas.c190770
基金项目: 国家自然科学基金(61773145, 61973098), 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)资助
详细信息
    作者简介:

    王桢榕:哈尔滨工业大学航天学院硕士研究生. 主要研究方向为基于模型的故障诊断. E-mail: arong_wang@163.com

    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. E-mail: zhenhua.wang@hit.edu.cn

    沈毅:哈尔滨工业大学航天学院教授. 主要研究方向为故障诊断, 飞行器控制, 超声信号处理. 本文通信作者. E-mail: shen@hit.edu.cn

Fault Isolability Evaluation Based on Zonotope

Funds: Supported by National Natural Science Foundation of China (61773145, 61973098) and the Key Laboratory Opening Funds of Harbin Institute of Technology (HIT.KLOF.2018.073)
More Information
    Author Bio:

    WANG Zhen-Rong Master student at the School of Astronautics, Harbin Institute of Technology. Her main research interest is model-based fault diagnosis

    WANG Zhen-Hua Associate professor at the School of Astronautics, Harbin Institute of Technology. His research interest covers fault diagnosis and fault-tolerant control

    SHEN Yi Professor at the School of Astronautics, Harbin Institute of Technology. His research interest covers fault diagnosis, flight vehicle control, and ultrasound signal processing. Corresponding author of this paper

  • 摘要: 针对包含幅值有界而分布形式未知的故障及输入干扰项的线性离散系统, 提出了一种新的系统故障可分离性的量化评价方法. 故障可分离性是故障可诊断性中的重要部分, 针对现有方法中基于方向相似度的故障可分离性评价方法存在的不足加以补充, 提出了利用中心对称多胞体对故障可分离性进行分析, 将中心对称多胞体集合转化为多面体的表示形式, 以达到对故障可分离性量化评价的目的, 同时给出了具体评价原理和评价指标. 最后, 通过数值仿真算例, 验证了该方法的有效性和优越性.
  • 图  1  各个故障模式组合下系统输出结果

    Fig.  1  System output results under the combination of various fault modes

    表  1  基于方向相似度可分离性评价结果(s = 5)

    Table  1  Fault isolability evaluation results based on directional similarity (s = 5)

    次数评价结果 次数评价结果 次数评价结果
    10.0977 60.7662 110.9239
    20.734570.0191120.3114
    30.138080.7235130.6323
    40.458090.1939140.3153
    50.2760100.4178150.2760
    下载: 导出CSV

    表  2  基于方向相似度可分离性评价结果(s = 500)

    Table  2  Fault isolability evaluation results based on directional similarity (s = 500)

    次数评价结果次数评价结果次数评价结果
    10.648160.6836110.6811
    20.648070.6885120.6734
    30.638080.6654130.6559
    40.629490.6294140.6289
    50.6698100.6168150.6610
    下载: 导出CSV

    表  3  数据分散程度评价

    Table  3  Evaluation of data dispersion

    窗口长度极差$(R)$标准差$(\sigma)$  窗口长度极差$(R)$标准差$(\sigma)$
    50.91280.2577  2250.16690.0349
    100.75190.17582500.13350.0297
    500.35010.08823750.12130.0278
    1000.29410.06044500.09140.0259
    1750.18980.05145000.07180.0226
    下载: 导出CSV

    表  4  基于方向相似度可分离性评价结果(s = 500)

    Table  4  Fault isolability evaluation results based on directional similarity (s = 500)

    故障$f_{1}$$f_{2}$$f_{3}$$f_{4}$
    $f_{1}$NULL1.00000.92360.4780
    $f_{2}$1.0000NULL0.92360.4780
    $f_{3}$0.92360.9236NULL0.6411
    $f_{4}$0.47800.47800.6411NULL
    下载: 导出CSV

    表  5  基于中心对称多胞体可分离性评价结果$(s=500)$

    Table  5  Fault isolability evaluation results based on Zonotope $(s=500)$

    故障$f_{1}$$f_{2}$$f_{3}$$f_{4}$
    $f_1$NULL1.00000.44640.1508
    $f_2$1.0000NULL0.44630.1508
    $f_3$0.44630.4463NULL0.3380
    $f_4$0.15080.15080.3380NULL
    下载: 导出CSV

    表  6  基于中心对称多胞体可分离性评价结果$(s=5)$

    Table  6  Fault isolability evaluation results based on Zonotope $(s=5)$

    故障$f_{1}$$f_{2}$$f_{3}$$f_{4}$
    $f_1$NULL1.00000.36650.2961
    $f_2$1.0000NULL0.36650.2961
    $f_3$0.36650.3665NULL0.3645
    $f_4$0.29610.29610.3645NULL
    下载: 导出CSV
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  • 收稿日期:  2019-11-07
  • 网络出版日期:  2020-12-17
  • 刊出日期:  2022-06-01

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