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浙江大学学报(工学版)
浙江大学学报(工学版)  2020, Vol. 54 Issue (4): 824-832    DOI: 10.3785/j.issn.1008-973X.2020.04.022
航空航天技术     
皮纳卫星姿控系统分层式故障检测
费云(),蒙涛*(),金仲和
浙江大学 航空航天学院，浙江 杭州 310027
Hierarchical fault detection for nano-pico satellite attitude control system
Yun FEI(),Tao MENG*(),Zhong-he JIN
School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, China
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摘要：

为了实现皮纳卫星的多故障在线检测，提出针对姿控系统的分层故障检测方案. 该方案将系统划分为系统层和器件层，系统层基于卫星动力学与运动学模型设计非线性观测器，实现姿控分系统故障的全局监测；器件层利用动力学模型设计数字动力学陀螺，结合卡尔曼算法新息以及小波分析，实现故障的定位. 通过分层检测，可以支持多器件故障的实时检测，能够检测常见的在轨姿态控制系统故障. 仿真结果表明，该方案能够实现多器件同时故障的检测，适应突变、偏差、恒增益、输出卡死等故障类型，检测准确率达到92%，误检率低于2%；由于采用假设检验取代阈值判断，相对于常规小波阈值检测方法，故障检测结果的可靠性更高，适应更多的故障类型，避免了阈值的选取问题，且节省计算资源，无需大量的历史信息，能够满足在线实时检测要求.
关键词： 皮纳卫星;  在线检测;  分层检测;  多器件故障;  小波变换    
Abstract:

A hierarchical fault detection scheme for attitude control system was proposed in order to realize the multi-fault online detection of nano-pico satellite. The system was divided into system layer and component layer. The system layer designed nonlinear observer based on satellite dynamics and kinematics model to realize the global monitoring of attitude control system faults. The component layer used dynamic model to design digital dynamic gyro. The fault location can be realized combined with the residual of Kalman algorithm and wavelet analysis. Multi-component faults can be detected in real time through hierarchical detection. The common on-orbit faults of the attitude control system can be detected. The simulation results show that the scheme can detect simultaneous faults of multiple components, and adapt to fault types such as sudden change, deviation, constant gain, output stuck, etc. The rate of fault detection accuracy reaches 92%, and the false detection rate is less than 2%. Due to the use of hypothesis testing instead of threshold judgment, the fault detection result is more reliable compared with the conventional wavelet detection method. The proposed scheme adapts to more fault types and avoids problems of threshold selection. The scheme saves computing resources, does not need a lot of historical information, and can meet the requirements of online real-time detection.
Key words: nano-pico satellite    online detection    hierarchical detection    multi-component fault    wavelet transform
收稿日期: 2019-01-14 出版日期: 2020-04-05
CLC:  V 448  
基金资助: 国家自然科学基金资助项目（61503334）；省级重点研发计划资助项目（209C05004）
通讯作者: 蒙涛     E-mail: fy927@zju.edu.cn;mengtao@zju.edu.cn
作者简介: 费云（1993—），男，博士生，从事微小卫星故障诊断的研究. orcid.org/0000-0003-2789-7404. E-mail： fy927@zju.edu.cn
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引用本文:

费云,蒙涛,金仲和. 皮纳卫星姿控系统分层式故障检测[J]. 浙江大学学报(工学版), 2020, 54(4): 824-832.

Yun FEI,Tao MENG,Zhong-he JIN. Hierarchical fault detection for nano-pico satellite attitude control system. Journal of ZheJiang University (Engineering Science), 2020, 54(4): 824-832.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2020.04.022    或    http://www.zjujournals.com/eng/CN/Y2020/V54/I4/824

图 1  姿控系统组成框图
图 2  分层检测方案
敏感器参数 参数值
陀螺（角度随机游走）nA 10?6 (°)/s1/2
陀螺（角速度随机游走）nR 10?8 (°)/s3/2
星敏感器噪声标准差σs [0.02, 0.003, 0.003]°
模拟太阳敏感器噪声标准差σsun 0.5 °
磁强计噪声标准差σm 10?8 T
表 1  敏感器模型参数
故障场景 故障器件 故障类型 故障时间/s
场景1 陀螺仪 突变故障 51
场景1 星敏感器 恒偏差故障 51
场景2 模拟太敏 无输出故障 112
场景2 磁强计 恒增益故障 112
场景2 飞轮 停转 112
表 2  故障场景说明
图 3  场景-系统层检测结果
图 4  场景-器件层检测结果
图 5  场景2的系统层检测结果
图 6  场景2的器件层检测结果
磁强计故障类型 状态 分层检测 小波阈值检测
故障 正常 故障 正常
卡死故障 故障 129 1 9 23
卡死故障 正常 21 149 141 127
偏差故障 故障 132 3 146 18
偏差故障 正常 18 147 4 132
增益故障 故障 144 0 147 31
增益故障 正常 6 150 3 119
表 3  2种检测方案的统计结果
故障类型 分层检测 常规小波阈值检测
准确率 误检率 漏检率 准确率 误检率 漏检率
卡死 92.7% 0.6% 14% 45% 15% 94%
偏差 93% 2% 12% 93% 12% 3%
增益 98% 0% 4% 89% 21% 2%
表 4  2种方案的检测效率对比
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