Machine Learning for Pre/Post Flight UAV Rotor Defect Detection Using Vibration Analysis

arXiv:2404.15880v1 Announce Type: cross
Abstract: Unmanned Aerial Vehicles (UAVs) will be critical infrastructural components of future smart cities. In order to operate efficiently, UAV reliability must be ensured by constant monitoring for faults and failures. To this end, the work presented in this paper leverages signal processing and Machine Learning (ML) methods to analyze the data of a comprehensive vibrational analysis to determine the presence of rotor blade defects during pre and post-flight operation. With the help of dimensionality reduction …

abstract aerial analysis arxiv cities components cs.lg defect detection detection eess.sp flight future machine machine learning monitoring paper processing reliability signal smart smart cities type unmanned aerial vehicles vehicles will work