Motion Primitive Approach to Rotorcraft Regime Recognition

This paper describes a novel approach to regime recognition based on the notion of motion primitives. Originally developed for path planning, motion primitives decompose a vehicle trajectory into maneuver and trim segments. In a regime recognition context, this decomposition can be used to improve component life tracking through separate classification of trim segments and maneuver segments. The proposed algorithm functions in three major steps. The first step consists of classifying the flight data into trim and maneuver segments. The second step leverages the information in the trim state and control vectors to classify each trim segment as a particular trim regime based on conditional logic. The final step makes use of dynamic time warping for the classification of each maneuver segment (flown between two trim segments) as a particular maneuver regime. Accuracy of the proposed algorithm is evaluated using simulated flight data for the SH-60B, and advantages of the proposed method compared to a threshold-based algorithm are assessed. The algorithm is also applied to actual flight data from a generic utility helicopter to demonstrate operation of the algorithm using real-world data.