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.