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Condition monitoring for flight performance estimation of small multirotor unmanned aerial vehicles

Wolfram, Daniel and Vogel, Florian and Stauder, Dominik (2018):
Condition monitoring for flight performance estimation of small multirotor unmanned aerial vehicles.
In: 2018 IEEE Aerospace Conference, Big Sky, MT, USA, USA, 3-10 March 2018, DOI: 10.1109/AERO.2018.8396471, [Online-Edition: https://ieeexplore.ieee.org/document/8396471/],
[Conference or Workshop Item]

Abstract

This study deals with a condition-based determination of small multirotor Unmanned Aerial Vehicles (UAV) flight performance. Knowledge of the actual flight performance enables an evaluation of mission risk for adaptive mission planners and an optimization of parameters for adaptive flight controllers. At the beginning of this paper basic principles of multicopter's flight mechanics are presented on the design of a X8 multicopter. The platform is designed as a quadcopter with redundant drives in coaxial configuration at each arm. The multicopter's flight performance is primarily influenced by its drive trains. A conventional drive train consists of accumulator, electronic speed controller, brushless direct current motor and propeller. Performance losses caused by faults or degradation of one of these components, directly affect the performance and safety of the entire multirotor UAV. This paper introduces a Condition Monitoring (CM) system, which examines the input and output power of the drive train's individual components by analyzing suitable sensor data. One important objective is the detection, isolation and identification of selected faults, which influence the power of the drive train. A test rig was developed to provide real data to investigate the fault behavior under laboratory conditions. Algorithms for sensor based flight performance estimation are first tested in a complex simulation environment. It consists of several modules, such as a model of the drive train with the possibility of simulating fault states, as well as a model of the complete research copter platform. Finally, the influence of technical faults on the multicopter's flight performance is presented.

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Wolfram, Daniel and Vogel, Florian and Stauder, Dominik
Title: Condition monitoring for flight performance estimation of small multirotor unmanned aerial vehicles
Language: English
Abstract:

This study deals with a condition-based determination of small multirotor Unmanned Aerial Vehicles (UAV) flight performance. Knowledge of the actual flight performance enables an evaluation of mission risk for adaptive mission planners and an optimization of parameters for adaptive flight controllers. At the beginning of this paper basic principles of multicopter's flight mechanics are presented on the design of a X8 multicopter. The platform is designed as a quadcopter with redundant drives in coaxial configuration at each arm. The multicopter's flight performance is primarily influenced by its drive trains. A conventional drive train consists of accumulator, electronic speed controller, brushless direct current motor and propeller. Performance losses caused by faults or degradation of one of these components, directly affect the performance and safety of the entire multirotor UAV. This paper introduces a Condition Monitoring (CM) system, which examines the input and output power of the drive train's individual components by analyzing suitable sensor data. One important objective is the detection, isolation and identification of selected faults, which influence the power of the drive train. A test rig was developed to provide real data to investigate the fault behavior under laboratory conditions. Algorithms for sensor based flight performance estimation are first tested in a complex simulation environment. It consists of several modules, such as a model of the drive train with the possibility of simulating fault states, as well as a model of the complete research copter platform. Finally, the influence of technical faults on the multicopter's flight performance is presented.

Uncontrolled Keywords: Rotors, Condition monitoring, Propellers, Unmanned aerial vehicles, Safety, Aircraft
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Flight Systems and Automatic Control (FSR)
Event Title: 2018 IEEE Aerospace Conference
Event Location: Big Sky, MT, USA, USA
Event Dates: 3-10 March 2018
Date Deposited: 03 Jul 2018 13:59
DOI: 10.1109/AERO.2018.8396471
Official URL: https://ieeexplore.ieee.org/document/8396471/
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