Characterization and Prognosis of Multirotor Failures

Multirotor (MR) unmanned aviation systems are becoming more prevalent in the commercial, philanthropic, and military communities. Because of these public environment applications, hardware malfunctions pose serious safety concerns. Propeller, motor, and structural damage can cause substantial failure of the MR vehicle and endanger surrounding people and structures; thus, early identification and prognosis of these failure modes is necessary to mitigate harm. An embedded structural health monitoring (SHM) system is optimal for identification and diagnosis of these failure modes in time to alter or abort the mission. To achieve autonomous SHM, statistical data must be accrued from a series of sensor measurements. This information is utilized in the development of appropriate damage metrics for failure modes of interest, which determine the real-time state of hardware elements. A comprehensive sensor network was successfully designed and implemented on an MR vehicle to determine which instruments provide valuable information. Utilizing this relevant data, a compatible set of tools was developed for signal processing, and the resulting SHM system is capable of classifying propeller, motor, and structural hardware failures.