Influence of Operationally Consumed Propellers on Multirotor UAVs Airworthiness: Finite Element and Experimental Approach
- 18 April 2023
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Sensors Journal
- Vol. 23 (11) , 11738-11745
Abstract
Unmanned aerial vehicles (UAVs) are widely used in many applications due to the current technological trend. In these applications, understanding the concept of the operating frequency range is vital to ensure UAV safety. Although most current studies are focused on health monitoring and fault diagnostic methodologies, none of them has included a comprehensive knowledge of the behavior of the natural frequency behavior. This research examines the effectiveness of computer-aided design (CAD) and computer-aided engineering (CAE) in advancing finite element modal analysis. Theoretical results were further evaluated on an experimentally operated drone to understand the interference concept of natural and operational frequencies. Extensive, high-quality, and comprehensive soft-labeled data was acquired in the time-domain from the selected hovering quad-copter equipped with an accelerometer sensor connected to a data acquisition system and a PC platform. Healthy propellers and operationally consumed propellers vibration signal datasets were recorded. The collected datasets were transformed to frequency-domain using Fast Fourier Transform (FFT) spectrum analysis. In summary, the finite element modal analysis provided a thorough behavior understanding of the faulty operating drone status by comparing the natural frequencies to those acquired experimentally based on a detailed discussion. The relationship between natural and operational frequencies is then investigated and presented.Keywords
This publication has 29 references indexed in Scilit:
- UAV Forensics: DJI Mini 2 Case StudyDrones, 2021
- Detection of REEs with lightweight UAV-based hyperspectral imagingScientific Reports, 2020
- UAV assistance paradigm: State-of-the-art in applications and challengesJournal of Network and Computer Applications, 2020
- Bearing Fault Diagnosis Using Motor Current Signature Analysis and the Artificial Neural NetworkInternational Journal on Advanced Science, Engineering and Information Technology, 2020
- A Drone Fleet-Borne SAR Model and Three-Dimensional Imaging AlgorithmIEEE Sensors Journal, 2019
- Assembling a Smart Phone Controlled Surveillance Unmanned Quadcopter2018
- Twin Rectangular Fork-Like Capacitance Sensor to Flow Regime Identification in Horizontal Co-Current Gas–Liquid Two-Phase FlowIEEE Sensors Journal, 2017
- The Development and Performance Characterization of Turbine Prototypes for a MEMS SpirometerIEEE Sensors Journal, 2015
- MEMS Multisensor Intelligent Damage Detection for Wind TurbinesIEEE Sensors Journal, 2014
- A Simulation of Non-stationary Signal Analysis Using Wavelet Transform Based on LabVIEW and Matlab2014