Publication | Closed Access
Parameter distribution characteristics of material fatigue life using improved bootstrap method
57
Citations
39
References
2018
Year
EngineeringLife PredictionMechanical EngineeringDeterioration ModelingFatigueReliability EngineeringData ScienceBiostatisticsMaterial Fatigue LifeReliability AnalysisStatisticsService Life PredictionReliabilityStructural Health MonitoringStructural ReliabilityLow-cycle FatigueBootstrap ResamplingImproved Bootstrap MethodBootstrap MethodSmall Sample DataParameter Distribution CharacteristicsStructural MechanicsMechanics Of MaterialsFailure Prediction
The bootstrap method is mostly used to estimate statistical characteristics of small sample data. However, the limitations of the bootstrap method itself lead to a reduction in the reliability of small-sample estimates. In this article, an improved bootstrap method is developed to address this problem. In the statistically significant error range (the sample average error and the limit error of sampling) of the original single sample data, expanding the virtual test data that obey two distributions to overcome the limitations of the bootstrap method itself. This article compares and analyses these two methods through the case; the result indicates that the improved bootstrap method can enhance the reliability of the estimation results without changing its probability distribution. We also discussed how to reduce the fluctuation of the improved bootstrap method. And the effectiveness and feasibility of this improved method are discussed in the analysis of fatigue life test data.
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