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NONLINEAR FAULT DIAGNOSIS OF JET ENGINES BY USING A MULTIPLE MODEL-BASED APPROACH

机译:基于多种模型的喷气发动机非线性故障诊断

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摘要

In this paper, a nonlinear fault detection and isolation (FDI) scheme that is based on the concept of multiple model (MM) approach is proposed for jet engines. A modular and a hierarchical architecture is proposed which enables the detection and isolation of both single as well as concurrent permanent faults in the engine. A set of nonlinear models of the jet engine in which compressor and turbine maps are used for performance calculations corresponding to various operating modes of the engine (namely, healthy and different fault modes) is obtained. Using the multiple model approach the probabilities corresponding to the engine modes of operation are first generated. The current operating mode of the system is then detected based on evaluating the maximum probability criteria. The performance of our proposed multiple model FDI scheme is evaluated by implementing both the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). Simulation results presented demonstrate the effectiveness of our proposed multiple model FDI algorithm for both structural and actuator faults in the jet engine.
机译:本文提出了一种基于多模型(MM)方法概念的喷气发动机非线性故障检测与隔离(FDI)方案。提出了一种模块化和分层的体系结构,该体系结构使得能够检测和隔离引擎中的单个以及同时存在的永久性故障。获得了喷气发动机的一组非线性模型,其中使用压缩机和涡轮映射来进行对应于发动机的各种运行模式(即正常和不同故障模式)的性能计算。使用多模型方法,首先生成与发动机运行模式相对应的概率。然后基于评估最大概率标准来检测系统的当前操作模式。通过实施扩展卡尔曼滤波器(EKF)和无味卡尔曼滤波器(UKF)来评估我们提出的多模型FDI方案的性能。给出的仿真结果证明了我们提出的多模型FDI算法对于喷气发动机中的结构故障和执行器故障的有效性。

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