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An unknown input Kalman filter based component FDI algorithm and its application in automobiles

机译:基于未知输入卡尔曼滤波器的组件FDI算法及其在汽车中的应用

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摘要

An Unknown Input Kalman Filter (UIKF) based Component Fault Detection and Isolation (CFDI) technique for a dynamical system, affected by both plant and measurement noise, is presented. The Fault Detection and Isolation (FDI) algorithm, which consists of two steps, is developed with the assumption that the fault occurs in a single component of the system. In step 1, the detection of the fault and the isolation of the faulty region are achieved. In the next step, the faulty parameter is isolated from the faulty region. The method is applied on a road vehicle model to show the effectiveness of the algorithm.
机译:提出了一种基于未知输入卡尔曼滤波器(UIKF)的动态系统组件故障检测和隔离(CFDI)技术,该技术受设备噪声和测量噪声的影响。故障检测和隔离(FDI)算法由两步组成,其开发假设故障发生在系统的单个组件中。在步骤1中,实现了故障的检测和故障区域的隔离。在下一步中,将故障参数与故障区域隔离。将该方法应用于道路车辆模型,证明了算法的有效性。

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