基于证据推理的联合故障检测方法
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作者单位:

西北工业大学自动化学院,西安710068.

作者简介:

程咏梅

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中图分类号:

V249.3

基金项目:

国家自然科学基金项目(61135001);西安市科技计划项目(CXY1436(9)).


Method of joint fault detection based on evidential reasoning
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School of Automation,Northwestern Polytechnical University,Xi’an 710068,China.

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    摘要:

    针对卡方故障检测方法对软故障的检测性能较差, 甚至会导致滤波器发散的问题, 提出一种基于证据推理的联合故障检测方法. 将组合导航中的各子滤波器作为证据, 利用每个子滤波器的状态及协方差构造联合故障检测函数, 并利用联合故障检测函数的概率分布计算基本置信指派, 再将多个证据按D-S 规则进行融合, 根据融合结果进行故障检测. 仿真结果表明, 所提出的方法对硬故障的检测性能与卡方故障检测性能相当, 但对软故障的检测性能要优于卡方故障检测, 可提高组合导航系统的可靠性和精度.

    Abstract:

    Aiming at the poor performance of chi-square fault detection for soft fault detection, even leading to the filter divergence problem, a joint fault detection method based on D-S evidential reasoning is proposed. Each sub filter in integrated navigation is used as the evidence. The state and the covariance of each sub filter are used for constructing the fault detection function and calculating the basic belief assignment. Then the fault detection is determined based on D-S fusion results. Simulation results show that the hard fault detection performance of this method has similar quality with the chi- square method. The soft fault detection performance is superior to the chi-square method, which can improve the reliability and accuracy of the integrated navigation system.

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牟宏磊 程咏梅 苟斌 刘建新 李松.基于证据推理的联合故障检测方法[J].控制与决策,2016,31(9):1589-1593

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历史
  • 收稿日期:2015-08-01
  • 最后修改日期:2015-12-26
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  • 在线发布日期: 2016-09-20
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