International Journal of Research in Advanced Electronics Engineering
2026, Vol. 7, Issue 1, Part A
Development of vibration-based fault detection system for brushless DC motors in small UAVs
Author(s): James W Patterson
Abstract: Brushless DC motors powering small unmanned aerial vehicles face demanding operational conditions that accelerate component degradation, with motor failure during flight presenting significant safety and economic consequences. Early detection of developing faults enables preventive maintenance scheduling and prevents catastrophic in-flight failures that could damage expensive airframes or create hazards in populated areas. This research presents the development and validation of a lightweight vibration-based fault detection system designed specifically for integration with small multi-rotor UAVs. The system employs dual MEMS accelerometers mounted at the motor base to capture three-axis vibration signatures, with an STM32F411 microcontroller performing real-time frequency domain analysis through 1024-point Fast Fourier Transform processing. Feature extraction algorithms compute statistical parameters including RMS amplitude, peak frequency, crest factor, kurtosis, and spectral entropy, feeding a decision tree classifier trained to distinguish healthy operation from three fault categories: rotor imbalance, bearing wear, and propeller damage. Validation testing across twelve 2212-class BLDC motors operating under controlled fault conditions achieved overall classification accuracy of 94.7%, with healthy motor identification reaching 97.1% accuracy. The system detected imbalance faults at amplitudes 2.8 times normal vibration levels with 93.3% accuracy, while bearing wear and propeller damage conditions were identified with 92.9% and 92.6% accuracy respectively. Detection latency under 50 milliseconds enables real-time fault alerting during flight operations. Field validation through 48 hours of accumulated flight testing across six UAV platforms demonstrated reliable fault detection without false alarms during normal operations, with two genuine developing faults successfully identified and confirmed through post-flight inspection. The complete sensor module weighs 28 grams and consumes 180 milliwatts, representing acceptable payload and power overhead for small UAV integration. The research provides UAV operators with a practical condition monitoring solution enabling transition from time-based to condition-based maintenance strategies, potentially reducing unscheduled maintenance events while improving operational safety through early warning of developing motor problems before flight-critical failures occur.
DOI: 10.22271/27084558.2026.v7.i1a.74
Pages: 33-38 | Views: 43 | Downloads: 21
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How to cite this article:
James W Patterson. Development of vibration-based fault detection system for brushless DC motors in small UAVs. Int J Res Adv Electron Eng 2026;7(1):33-38. DOI: 10.22271/27084558.2026.v7.i1a.74
