Conditional Averaging Methodology for Periodic Data with Time Jitter and Spatial Scatter

Abstract

In helicopter rotor experimental data - either originating from the flying helicopter or from the wind tunnel model -– periodic and non-periodic motions of the test vehicle are present due to gusts and transient motion of the helicopter or due to flexibility of model support and unsteadiness in the wind tunnel environment. These motions usually are of low-frequency nature compared to the rotor rotational frequency, but they slightly change the aerodynamic environment revolution by revolution. Consequently the data like rotor blade position, blade pressure, vortex position, microphone pressure exhibit disturbances in space and/or time that must properly be addressed in data analysis, especially when the time (or space) averaged data are to be computed. These averaged data (velocity fields, position or pressure time histories) are the basis for code validation efforts and thus special algorithms must be applied to eliminate these spatial scatter and/or time jitter effects appropriately.