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Flex Seal Stiffness Estimation in Flex Nozzle Control System Using Extended Kalman Filter

机译:使用扩展卡尔曼滤波器的柔性喷嘴控制系统中的柔性密封刚度估算

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This paper presents the application of Extended Kalman Filter (EKF) for detection of flex seal stiffness fault in Electro Hydraulic Actuator (EHA) driven Flex Nozzle Control (FNC) system. The extended Kalman filter is applied to the EHA to estimate the states as well as parameter (flex seal stiffness). It should be highlighted that the servo valve current is used instead of the desired piston position as the input to the EKF in order to simplify the state estimation problem which would have otherwise involved a fifth order model. The EKF-based estimator includes complete nonlinear models of hydraulic functions. It is shown that, firstly, under normal (no fault) operating condition, the developed estimator closely predicts the states of the system, using only a few basic measurements. Secondly, in the presence of seal stiffness fault, the level of residual errors between the estimated and the actual seal stiffness, increase significantly indicating the occurrence of fault. The results demonstrate the efficacy of the proposed EKF-based fault detection scheme to promptly and reliably respond to flex nozzle control systems seal stiffness fault.
机译:本文介绍了扩展卡尔曼滤波器(EKF)在检测电动液压执行器(EHA)驱动的柔性喷嘴控制(FNC)系统中的柔性密封刚度故障中的应用。将扩展的卡尔曼滤波器应用于EHA以估计状态以及参数(弹性密封刚度)。应该强调的是,使用伺服阀电流代替期望的活塞位置作为EKF的输入,以简化状态估计问题,否则状态估计问题将涉及五阶模型。基于EKF的估算器包括液压功能的完整非线性模型。结果表明,首先,在正常(无故障)操作条件下,开发的估算器仅使用一些基本测量就可以紧密预测系统的状态。其次,在存在密封刚度故障的情况下,估计的密封刚度和实际密封刚度之间的残留误差水平显着增加,表明发生了故障。结果证明了所提出的基于EKF的故障检测方案能够迅速,可靠地响应柔性喷嘴控制系统的密封件刚度故障。

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