| 引用本文: | 牛艺春,刘诗洋,高明,盛立.线性随机系统的微小传感器故障检测[J].控制理论与应用,2022,39(5):879~886.[点击复制] |
| NIU Yi-chun,LIU Shi-yang,GAO Ming,SHENG Li.Incipient sensor fault detection for linear stochastic systems[J].Control Theory and Technology,2022,39(5):879~886.[点击复制] |
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| 线性随机系统的微小传感器故障检测 |
| Incipient sensor fault detection for linear stochastic systems |
| 摘要点击 1625 全文点击 569 投稿时间：2021-06-21 修订日期：2022-02-12 |
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| DOI编号 10.7641/CTA.2021.10534 |
| 2022,39(5):879-886 |
| 中文关键词 随机系统 微小故障检测 可检测性分析 移动加权平均方法 |
| 英文关键词 stochastic systems incipient fault detection detectability analysis weighted moving average method |
| 基金项目 国家自然科学基金项目(62173343, 62073339, 62033008), 山东省自然科学基金项目(ZR2020YQ49)资助. |
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| 中文摘要 |
| 针对一类线性随机系统, 研究了其微小传感器故障检测问题. 基于Kalman滤波算法构造状态估计器, 利用
移动加权平均方法设计残差与评价函数. 根据非中心卡方分布的性质, 分析了故障幅值、窗口长度、误报率和漏报
率之间的关系. 采用不等式技术, 得到了确保在统计意义下微小故障可检测性的最优权值和最小窗口长度. 最后, 通
过一个仿真实例验证了所提方法的有效性. |
| 英文摘要 |
| In this paper, the problem of incipient sensor fault detection is investigated for linear stochastic systems. The
state estimator is constructed by using the Kalman filtering algorithm. Then, the residual and the evaluation function are
designed by means of the weighted moving average method. According to the property of the non-central χ2 distribution,
the relationships among the fault amplitude, the window length, the false alarm rate and the missed detection rate are
analyzed. By using the inequality technique, the optimal weights and the minimum window length, which ensure the
detectability of incipient faults in a probabilistic sense, are derived. Finally, an illustrative example is provided to verify the
effectiveness of the proposed method. |
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