Vibration-based structural anomaly detection and health monitoring of urban air mobility vehicles

The urban air mobility (UAM) market continues to grow as the importance of structural health monitoring (SHM) technology is increasingly emphasized for safe operation. This study proposes a Euclidean distance vector-based vibration analysis method for the early detection of abnormal vibrations and for performing safety diagnostics in the rotor-arm system of a multicopter-type UAM. Vibration experiments were conducted by simulating abnormal conditions such as mass imbalance, bolt loosening, and propeller damage in stages to verify this approach, thereby reflecting actual operating environments. The frequency response and vibration characteristics were analyzed in comparison to normal conditions. The analysis showed that even minor mass imbalances and bolt loosening caused a significant increase in vibration within specific frequency bands. Certain frequency bands exhibited pronounced damping effects as damage worsened, revealing complex dynamic behavior. These results confirm shifts in resonance frequency and dispersion of vibration energy due to structural dynamic changes, thereby demonstrating the effectiveness of the Euclidean distance vector-based analysis method in detecting such anomalies. In conclusion, the proposed method enables the early detection of anomalies in multicopter-type UAM rotor arms, providing a basis for safety diagnostics and potentially enhancing reliability through expansion into fault detection systems.