Determination of Turboprop Reduction Gearbox System Fatigue Life and Reliability

Abstract

Two computational models to determine the fatigue life and reliability of a commercial turboprop gearbox are compared with each other and with field data. These models are (1) Monte Carlo simulation of randomly selected lives of individual bearings and gears comprising the system and (2) two-parameter Weibull distribution function for bearings and gears comprising the system using strict-series system reliability to combine the calculated individual component lives in the gearbox. The Monte Carlo simulation included the virtual testing of 744,450 gearboxes. Two sets of field data were obtained from 64 gearboxes that were first-run to removal for cause, were refurbished and placed back in service, and then were second-run until removal for cause. A series of equations were empirically developed from the Monte Carlo simulation to determine the statistical variation in predicted life and Weibull slope as a function of the number of gearboxes failed. The resultant L ₁₀ life from the field data was 5,627 h. From strict-series system reliability, the predicted L ₁₀ life was 774 h. From the Monte Carlo simulation, the median value for the L ₁₀ gearbox lives equaled 757 h. Half of the gearbox L ₁₀ lives will be less than this value and the other half more. The resultant L ₁₀ life of the second-run (refurbished) gearboxes was 1,334 h. The apparent load-life exponent p for the roller bearings is 5.2. Were the bearing lives to be recalculated with a load-life exponent p equal to 5.2, the predicted L ₁₀ life of the gearbox would be equal to the actual life obtained in the field. The component failure distribution of the gearbox from the Monte Carlo simulation was nearly identical to that using the strict-series system reliability analysis, proving the compatibility of these methods.

KEY WORDS:

• Gearbox Life Prediction
• Gearing
• Rolling-Element Bearings
• Monte Carlo Analysis
• Probabilistic Life Analysis
• Weibull Analysis

Acknowledgments

Review led by Bob Errichello

Notes

^a At a 53.5% probability of failure.

^b At a 59.3% probability of failure.

^c At a 61.4% probability of failure.