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A model based approach for sensor fault detection in civil aircraft control surface

机译:基于模型的民航飞机操纵面传感器故障检测方法

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A model-based fault detection and diagnosis (FDD) solution improves the capability in a civil aircraft control surface whereas having low complexity and computational requirements. The main objective of the FDD. techniques that are extensively applied in industrial systems is to increase the sensitivity of fault detection scheme while maintaining a reliable system response with respect to additional unknown inputs. In the paper, a reformative approach to an observer-based fault detection method is introduced for FDD. As an effect of the stochastic attitude of the variables due to the noisy characteristics of some elements in the system and model uncertainties such as parametric uncertainty or unmodeled dynamics, false alarms are indicated and upon a new approach is practiced to attenuate the false alarm rates. The reliability of the available method is increased by choosing appropriate parameters with respect to the measurement noise and modelling errors. The designed fault detection model is integrated to a nonlinear civil aircraft model of Boeing 747 with a proper tuning of parameters. The system is developed in MATLAB Simulink and mainly consist of a closed-loop aircraft model to verify the effectiveness of the sensor fault detection technique, an observer to estimate the states of the aircraft during steady state flight, a fault indicator to propagate faulty responses to the system and a reconfigurator to identify the flight condition if it is fault-free or faulty by comparing the states which are achieved from the sensor of the control surface in real-time and provided from the flight control law computation. Fault detection is accomplished by evaluating any significant change in the behavior of the aircraft with respect to the fault-free behavior which is estimated by using a standard Kalman filter as an observer. The scheme presented based on Kalman filter composes a residual sensitive to fault incidents and maintains a reliable fault detection approach incororating the rejection of false alarm that is required for system reliability. The developed method is a viable solution for earlier control surface stuck detection to lower threshold amplitude as an outcome of multisimulation tests performed in MATLAB Simulink.
机译:基于模型的故障检测与诊断(FDD)解决方案提高了民用飞机控制面的能力,同时具有较低的复杂性和计算要求。 FDD的主要目标。在工业系统中广泛应用的技术是提高故障检测方案的灵敏度,同时针对其他未知输入保持可靠的系统响应。在本文中,针对FDD引入了一种基于观察者的故障检测方法的革新方法。由于系统中某些元素的噪声特性以及模型不确定性(例如参数不确定性或未建模的动力学)对变量的随机态度的影响,因此会显示错误警报,并且在采用新方法以降低错误警报率的情况下。通过针对测量噪声和建模误差选择适当的参数,可以提高可用方法的可靠性。通过适当的参数调整,将设计的故障检测模型集成到波音747的非线性民航飞机模型中。该系统是在MATLAB Simulink中开发的,主要包括一个用于验证传感器故障检测技术有效性的闭环飞机模型,一个观察员以估计稳态飞行期间飞机的状态,一个故障指示器以将故障响应传播到该系统和重新配置器通过实时比较从控制面传感器获得的状态和由飞行控制律计算提供的状态,来确定飞行状态是否无故障或有故障。通过评估飞机行为相对于无故障行为的任何重大变化(通过使用标准卡尔曼滤波器作为观察者进行估算),可以完成故障检测。基于卡尔曼滤波器的方案提出了一种对故障事件敏感的残差,并维持了一种可靠的故障检测方法,该方法与拒绝系统可靠性所需的虚假警报相关。所开发的方法是一种可行的解决方案,可作为在MATLAB Simulink中执行的多次仿真测试的结果,从而将控制面早期卡死检测到较低的阈值幅度。

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