首页> 外文会议>Congress of the International Council of the Aeronautical Sciences; 20060903-08; Hamburg(DE) >STATISTICAL FAULT DETECTION AND IDENTIFICATION IN AIRCRAFT SYSTEMS VIA FUNCTIONALLY POOLED NONLINEAR MODELLING OF FLIGHT DATA DEPENDENCIES
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STATISTICAL FAULT DETECTION AND IDENTIFICATION IN AIRCRAFT SYSTEMS VIA FUNCTIONALLY POOLED NONLINEAR MODELLING OF FLIGHT DATA DEPENDENCIES

机译:通过功能性飞行数据的非线性非线性建模对飞机系统中的统计故障进行识别

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摘要

A Fault Detection and Identification (FDI) scheme for aircraft systems based on the modelling of relationships among flight variables is introduced. The modelling is performed by means of Time-dependent Functionally Pooled Nonlinear AutoRegressive with exogenous (TFP-NARX) excitation representations. These are generalized NARX representations with (a) their parameters being functions of time-dependent flight variables and (b) the capability of describing a system under various operating conditions due to their pooled form. During the system's operation in healthy mode, these relationships are valid. Hence a scheme using statistical hypothesis testing is designed to detect changes in the relationships due to potential fault occurrence. The FDI scheme's performance and robustness are assessed with flights conducted under various flight conditions.
机译:介绍了一种基于飞行变量之间关系建模的飞机系统故障检测与识别(FDI)方案。建模是通过具有外源(TFP-NARX)激励表示的时变功能池非线性自回归进行的。这些是广义的NARX表示形式,(a)其参数是随时间变化的飞行变量的函数,(b)由于其合并形式而具有在各种运行条件下描述系统的能力。在系统以健康模式运行时,这些关系有效。因此,使用统计假设检验的方案被设计为检测由于潜在故障发生而导致的关系变化。通过在各种飞行条件下进行的飞行来评估FDI计划的性能和稳健性。

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