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

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.

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