Yong Keong Yap

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2014-70

May 14, 2014

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-70.pdf

Currently, drones are not very reliable systems. This paper presents a sensor system to detect motor defects on drones to overcome this deficiency. The feasibility of installing micro-electromechanical (MEMS) accelerometers on drones to inspect the vibration characteristics of a drone is investigated. Accelerometers were installed near the drone motors to collect vibration data and a Fourier Fast Transform (FFT) was used to analyze the data. An empirical method of observing the vibration spectrum of an Unmanned Aerial Systems (UAS) airframe was demonstrated by adopting motor vibration measurement methods. A baseline condition for what constitutes proper operation was first made. Airframes that were intentionally damaged showed significant differences in vibration spectrum, demonstrating that a cheap and feasible failure prediction and detection warning system can be applied to small scale UAS.

Advisors: Raja Sengupta and David Allstot

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BibTeX citation:

@mastersthesis{Yap:EECS-2014-70,
    Author= {Yap, Yong Keong},
    Title= {Structural Health Monitoring For Unmanned Aerial Systems},
    School= {EECS Department, University of California, Berkeley},
    Year= {2014},
    Month= {May},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-70.html},
    Number= {UCB/EECS-2014-70},
    Note= {Please use this version. The other 2 have an error in the submission options.},
    Abstract= {Currently, drones are not very reliable systems. This paper presents a sensor system to detect motor defects on drones to overcome this deficiency. The feasibility of installing micro-electromechanical (MEMS) accelerometers on drones to inspect the vibration characteristics of a drone is investigated. Accelerometers were installed near the drone motors to collect vibration data and a Fourier Fast Transform (FFT) was used to analyze the data. An empirical method of observing the vibration spectrum of an Unmanned Aerial Systems (UAS) airframe was demonstrated by adopting motor vibration measurement methods. A baseline condition for what constitutes proper operation was first made. Airframes that were intentionally damaged showed significant differences in vibration spectrum, demonstrating that a cheap and feasible failure prediction and detection warning system can be applied to small scale UAS.},
}

EndNote citation:

%0 Thesis
%A Yap, Yong Keong 
%T Structural Health Monitoring For Unmanned Aerial Systems
%I EECS Department, University of California, Berkeley
%D 2014
%8 May 14
%@ UCB/EECS-2014-70
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-70.html
%F Yap:EECS-2014-70