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1)  robust fault detection
鲁棒故障检测
1.
Robust fault detection for networked systems with uncertain missing measurements probabilities;
测量丢失概率不确定的网络化系统的鲁棒故障检测
2.
To investigates the problem of robust fault detection for a class of uncertain large-scale system,the objective is to minimize the difference between the residual and the weighted fault and to enhance the robustness to dynamic interconnected terms、control inputs and model uncertainties,The existence condition of the filter is established by means of linear matrix linear matrix inequalities.
讨论了不确定性关联大系统的鲁棒故障检测问题,使残差信号和加权故障信号之间的误差最小,并对动态关联项、控制输入和系统的不确定性具有鲁棒性进行了探讨,应用线性矩阵不等式得到此类不确定性系统的鲁棒故障检测滤波器的存在条件。
3.
This paper is concerned with the problem of robust fault detection for a class of discrete-time systems with norm-bounded uncertainties and time delays in state.
针对具有范数有界不确定性和状态时滞的离散系统,研究了基于滤波器的鲁棒故障检测问题。
2)  Robustness fault detection
鲁棒性故障检测
3)  robust fault detection and isolation
鲁棒故障检测与分离
1.
A parametric observer-based approach for robust fault detection and isolation in multivariable linear systems with unknown disturbances is proposed.
针对具有未知干扰输入的多变量线性系统,提出一种鲁棒故障检测与分离的完全参数化方法。
2.
A new parametric observer-based approach for robust fault detection and isolation in linear time-delay systems with unknown disturbances is proposed.
针对一类具有未知干扰输入的时滞线性系统,提出一种鲁棒故障检测与分离的完全参数化方法。
4)  filter for robust fault detection
鲁棒故障检测滤波器
5)  robust fault observer
鲁棒故障观测器
6)  Robust fault reconstructing observer
鲁棒故障重构观测器
补充资料:故障检测
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性质:对故障诊断中所需的各种信号进行检测的过程。是一门应用型的边缘学科,它的理论基础是现代控制理论、计算机工程、数理统计、信号处理、模式识别、人工智能以及相应的应用学科。主要方法分基于系统动态模型的方法和不依赖于动态模型的方法。其中后者又分为:(1)直接测量系统的输入输出;(2)基于因果关系的信号处理方法;(3)基于专家系统的方法;(4)基于故障树的诊断方法;(5)基于模式识别的诊断方法;(6)基于模糊数学的诊断方法;(7)基于人工神经元网络的方法。

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