Quantification of motor failure influence on quad-rotor crash area using statistical analysis

Quad-rotor unmanned aerial vehicles (UAVs) have impacted various industries with their advanced capabilities. However, they are not immune to failures that can occur during operation. Existing literature lacks sufficient research on the effects of partial propulsion failures and their implications o...

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Bibliographic Details
Main Authors: Sivakumar, Anush Kumar, Thanaraj, T., Feroskhan, Mir
Other Authors: School of Mechanical and Aerospace Engineering
Format: Conference Paper
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/172634
Description
Summary:Quad-rotor unmanned aerial vehicles (UAVs) have impacted various industries with their advanced capabilities. However, they are not immune to failures that can occur during operation. Existing literature lacks sufficient research on the effects of partial propulsion failures and their implications on crash areas, indicating a knowledge gap that necessitates extensive investigation into the descent dynamics of quad-rotors. Consequently, this study quantitatively examines the influence of a single motor and complete power failure on the crash area of a quad-rotor aircraft. Statistical analyses were performed on datasets obtained from multi-domain dynamic flight simulations executed on MATLAB Simulink. Findings revealed that both failure mode and initial speed had significant main effects on the crash area, accounting for 40.7% and 97.1% of the variance, respectively. At initial speeds of 8 to 18 m/s, quad-rotors with single motor failure exhibited a larger crash area compared to complete power failure. Moreover, single motor failure on the adjacent motor pairs (front and back) demonstrated no significant influence on the crash area. This implies that the crash areas are statistically equivalent for single motor failure on adjacent motor pairs. Overall, the results from this study enhance our understanding of quad-rotor descent and crash dynamics, particularly in the context of single motor failure and complete power failure. These insights can potentially guide the development of UAV risk assessments, mitigate catastrophic accidents, and improve the reliability of operations in urban environments.