An Exploration of Discontinuous Time Synchronous Averaging for Helicopter HUMS Using Cruise and Terminal Area Vibration Data
Recent research using NASA Ames AH-1 and OH-58C helicopters, and NASA Glenn test rigs, has shown that in-flight vibration data are typically non-stationary [l-4]. The nature and extent of this non-stationarity is most likely produced by several factors operating simultaneously. The aerodynamic flight environment and pilot commands provide continuously changing inputs, with a complex dynamic response that includes automatic feedback control from the engine regulator. It would appear that the combined effects operate primarily through an induced torque profile, which causes concomitant stress modulation at the individual internal gear meshes in the transmission. This notion is supported by several analyses, which show that upwards of 93% of the vibration signal s variance can be explained by knowledge of torque alone. That this relationship is stronger in an AH-1 than an OH-58, where measured non-stationarity is greater, suggests that the overall mass of the vehicle is an important consideration. In the lighter aircraft, the unsteady aerodynamic influences transmit relatively greater unsteady dynamic forces on the mechanical components, quite possibly contributing to its greater non-stationarity . In a recent paper using OH-58C pinion data [5], the authors have shown that in computing a time synchronous average (TSA) for various single-value metric computations, an effective trade-off can be obtained between sample size and measured stationarity by using data from only a single mesh cycle. A mesh cycle, which is defined as the number of rotations required for the gear teeth to return to their original mating position, has the property of representing all of the discrete phase angles of the opposing gears exactly once in the average. Measured stationarity is probably maximized because a single mesh cycle of the pinion gear occurs over a very short span of time, during which time-dependent non-stationary effects are kept to a minimum. Clearly, the advantage of local stationarity diminishes as the temporal duration of the cycle increases. This is most evident for a planetary mesh cycle, which can take several minutes to complete.