Pilots, mostly the beginner ones, often overlook the maintenance of the unmanned aerial vehicle (UAV). A lack of proper maintenance or condition monitoring before flying the UAV might lead to a crash due to failures in certain UAV components. Besides, the drone inspection based on the naked eyes is unreliable as some faults might be missed. In this study, the real-time data collection technique for propeller’s inspection is introduced. An ADXL345 accelerometer was used to determine the acceleration experienced by the UAV and classify between a healthy and faulty propeller in real-time. Currently, this approach does not require further signal processing techniques as the faulty propeller can be detected from raw acceleration data. The results show that the ADXL345 accelerometer can classify between four types of faulty propellers simulated in this study and is preferable to be implemented compared to using the infrared sensor. Based on the experimental results, an improvement of 15.64% was determined in terms of the minimum difference between healthy and faulty data.


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    Title :

    Real-Time Data Collection Technique for UAVs Propeller Inspection


    Additional title:

    Lect. Notes Electrical Eng.




    Publication date :

    2022-07-07


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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