On-board Health-state Awareness to Detect Degradation in Multirotor Systems

This paper presents the development and demonstration of an on-board health-state awareness technology that can predict degradation over the dynamic operational life of the vehicle. We established the feasibility of replacing the standard electronic speed control on a small UAV with an Intelligent Electronic Speed Control (IESC) that uses the telemetry data from sensors to develop an intelligent rule set extracted from a trained artificial neural network to detect propulsion system degradation, predict specific types of failures by analyzing sensor data collected from the motor and ESC, and access life cycle characteristics for a UAV propulsion system. The IESC will improve performance and reliability, increase safety and decrease maintenance costs by detecting issues prior to flight. The long term goal of the project is to be able to predict failures across families of small UAV based upon historic performance data that can be shared among users.