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An approach to vibration analysis using wavelets in an application of aircraft health monitoring

机译:小波振动分析在飞机健康监测中的应用

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This paper explores an application of vibration detection in aircraft. Fatigue and breakdown of aircraft structure are common. Thus, efforts are made to constantly improve the monitoring and diagnostic systems for aircraft. These improvements have led to various approaches to fault monitoring in aircraft. In this work, the characteristic features of vibration signals are extracted from noise using the Haar. Daubechies, and Morlet wavelets. Then, detection of the vibration signal is achieved using the signal's scalogram information. Based on initial results, the wavelet-based algorithm is optimised through threshold experimentation. Additionally, the algorithm is verified using the simulation of a sinusoidal waveform and real flight data from the F-15B/836 research airplane.
机译:本文探讨了振动检测在飞机上的应用。飞机结构的疲劳和故障很常见。因此,致力于不断改进飞机的监视和诊断系统。这些改进导致了飞机故障监测的各种方法。在这项工作中,使用Haar从噪声中提取振动信号的特征。 Daubechies和Morlet小波。然后,使用信号的比例尺信息实现振动信号的检测。基于初始结果,通过阈值实验对基于小波的算法进行了优化。此外,该算法使用正弦波形仿真和F-15B / 836研究飞机的真实飞行数据进行了验证。

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