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核主元分析在航天器飞轮自主故障诊断的应用

聂小辉 金磊

聂小辉,金磊. 核主元分析在航天器飞轮自主故障诊断的应用[J]. 北京航空航天大学学报,2023,49(8):2119-2128 doi: 10.13700/j.bh.1001-5965.2021.0582
引用本文: 聂小辉,金磊. 核主元分析在航天器飞轮自主故障诊断的应用[J]. 北京航空航天大学学报,2023,49(8):2119-2128 doi: 10.13700/j.bh.1001-5965.2021.0582
NIE X H,JIN L. Application of kernel principal component analysis in autonomous fault diagnosis for spacecraft flywheel[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(8):2119-2128 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0582
Citation: NIE X H,JIN L. Application of kernel principal component analysis in autonomous fault diagnosis for spacecraft flywheel[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(8):2119-2128 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0582

核主元分析在航天器飞轮自主故障诊断的应用

doi: 10.13700/j.bh.1001-5965.2021.0582
详细信息
    通讯作者:

    E-mail:jinleibuaa@163.com

  • 中图分类号: V448.22;TP277

Application of kernel principal component analysis in autonomous fault diagnosis for spacecraft flywheel

More Information
  • 摘要:

    针对在轨航天器执行机构故障诊断研究相对较少、姿态控制系统背景建模相对简单、算法自主性不强等问题,提出一种基于核主元分析(KPCA)的飞轮自主故障诊断方法。建立使用飞轮组的刚体航天器三轴稳定姿态控制系统;在力矩模式和转速模式下分别建立飞轮伺服系统,并给出飞轮常见故障及其模型;在上述模式下分别采集飞轮组输入输出的差值数据,进行同源扩维,通过改进特征向量归一化准则,优化了KPCA统计量法,并建立一种综合指标,通过比对该指标是否超限判断有无故障,减少对单一指标的主观侧重;在经典的贡献图法基础上进行溯源合并,计算综合贡献率,以此定位故障飞轮。仿真结果表明:所提方法能够实现航天器飞轮自主故障诊断,2种模式下,正确率较传统方法分别平均提高约40.94%、22.23%,适用于单点故障、多点故障、轻微故障等多种情况。

     

  • 图 1  力矩模式下时滞参数对量化指标影响示意图

    Figure 1.  Diagram of influence of delay parameter on quantitative index in torque mode

    图 2  力矩模式下单一统计量随时间的变化

    Figure 2.  Variation of single statistic with time in torque mode

    图 3  力矩模式下综合指标随时间的变化

    Figure 3.  Variation of comprehensive index with time in torque mode

    图 4  力矩模式下指定时刻综合贡献率示意图

    Figure 4.  Diagram of comprehensive contribution rate at specified time in torque mode

    图 5  转速模式下时滞参数对量化指标影响示意图

    Figure 5.  Diagram of influence of delay parameter on quantitative index in speed mode

    图 6  转速模式下单一统计量随时间的变化

    Figure 6.  Variation of single statistic with time in speed mode

    图 7  转速模式下综合指标随时间的变化

    Figure 7.  Variation of comprehensive index with time in speed mode

    图 8  转速模式下指定时刻综合贡献率示意图

    Figure 8.  Diagram of comprehensive contribution rate at specified time in speed mode

    表  1  飞轮常见故障及模型

    Table  1.   Common faults and models of flywheel

    序号ewfw故障特征故障类型
    100转速不变或渐趋0空转
    200转速迅速归0卡死
    31$ \ne 0 $输入输出存在偏差偏差故障
    4$ (0,1) $0输入输出按比减小增益故障
    5不定不定无固定特征混合故障
    下载: 导出CSV

    表  2  飞轮基本参数

    Table  2.   Basic parameters of flywheel

    转动惯量/
    (kg·m2
    电枢
    电阻/$ \Omega $
    转矩系数/
    (N·m·A−1
    反电动势系数/
    (V·s·rad−1
    0.007720.0290.029
    下载: 导出CSV

    表  3  飞轮故障参数

    Table  3.   Fault parameters of flywheels

    故障时间/s故障类型ewfw/(N·m)故障部位
    550~600空转00飞轮1
    450~500偏差故障1−0.0003飞轮2
    350~400增益故障0.150飞轮3
    350~500偏差故障1−0.0003飞轮3
    下载: 导出CSV

    表  4  力矩模式下时滞参数为2时不同指标性能对比

    Table  4.   Performance comparison of different indexes when number of delay parameter is 2 in torque mode %

    判定准则误报率漏报率正确率
    T2超限1.5011.5591.80
    SPE超限2.6074.0049.80
    T2、SPE同时超限0.2074.5050.27
    综合指标超限4.6011.2590.97
    下载: 导出CSV

    表  5  转速模式下时滞参数为2时不同指标性能对比

    Table  5.   Performance comparison of different indexes when number of delay parameter is 2 in speed mode %

    判定准则误报率漏报率正确率
    T2超限6.400.1097.80
    SPE量超限6.1037.9072.70
    T2、SPE同时超限0.7037.9074.50
    综合指标超限12.300.1095.83
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-09-30
  • 录用日期:  2021-12-20
  • 网络出版日期:  2022-01-19
  • 整期出版日期:  2023-08-31

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