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首页> 外文会议>Congress of the International Council of the Aeronautical Sciences; 20060903-08; Hamburg(DE) >USING DETECTION INDICES (DI) TO DETECT AIR VEHICLE CHARACTERISTIC CHANGES FOR HUMS APPLICATION
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USING DETECTION INDICES (DI) TO DETECT AIR VEHICLE CHARACTERISTIC CHANGES FOR HUMS APPLICATION

机译：使用检测指数（DI）检测用于HUMS的航空特性变化

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摘要

This paper presents the application of 'Detection Indices' (DI) to monitor the health and usage aspects of air vehicles. The two DI described in this paper utilise 'Autocorrelation' and 'Cross-Correlation' algorithms. The primary function of the autocorrelation process in this context is to precondition the raw data segments obtained from the monitored data stream into a format that allows accurate comparison between two consecutive data segments. The second type of DI is the cross-correlation. The main emphasis of the cross-correlation analysis is to verify if differences exist between the two compared autocorrelated data sets, thus indicating whether changes have occurred in the characteristics of the vehicle being monitored. The described DI will eventually be imbedded in a miniaturised HUMS unit, called SmartHUMS, currently under development by the Defence Science and Technology Organisation (DSTO) in-cooperation with GPS Online Pty Ltd. A number of experimental results obtained by the preproduction SmartHUMS unit are presented in this paper. The experimental test setups used for the experiments consist of a bench top electric motor driven test rig and a two-stroke model helicopter engine driven experimental test rig. During the bench top electric motor and model helicopter engine experiments, artificial disturbance was introduced to demonstrate the DI algorithm's ability to detect the disturbance. This paper presents the result for each of these experiments and show that the proposed DI can be used to create a low-cost HUMS solution.
机译：本文介绍了“检测指标”（DI）在监控飞行器的健康和使用方面的应用。本文介绍的两个DI使用“自相关”和“交叉相关”算法。在这种情况下，自相关过程的主要功能是将从受监视的数据流中获得的原始数据段预处理为一种格式，该格式允许在两个连续的数据段之间进行精确比较。 DI的第二种类型是互相关。互相关分析的主要重点是验证两个比较的自相关数据集之间是否存在差异，从而表明被监控车辆的特性是否发生了变化。所描述的DI最终将被嵌入到名为HUSM的小型HUMS单元中，该单元目前由国防科学技术组织（DSTO）与GPS Online Pty Ltd合作开发。试生产的SmartHUMS单元获得的许多实验结果如下：在本文中提出。用于实验的实验测试装置包括台式电动机驱动的试验台和两冲程模型直升机发动机驱动的试验台。在台式电动机和直升机模型发动机实验期间，引入了人工干扰来证明DI算法检测干扰的能力。本文介绍了每个实验的结果，并表明所提出的DI可用于创建低成本HUMS解决方案。

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