首页|Time-dependent reliability analysis of aerospace electromagnetic relay considering hybrid uncertainties quantification of probabilistic and interval variables
Time-dependent reliability analysis of aerospace electromagnetic relay considering hybrid uncertainties quantification of probabilistic and interval variables
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Time-dependent reliability analysis of aerospace electromagnetic relay considering hybrid uncertainties quantification of probabilistic and interval variables
Reliability is a crucial metric in aerospace engineering.The results of reliability assess-ments for components like aerospace electromagnetic relays directly impact the development and operational reliability of aerospace engineering systems.Current methods for analyzing the reliabil-ity of aerospace electromagnetic relays have limitations,such as neglecting the combined effects of multiple uncertain factors,degradation of key component properties,and the influence of fluctua-tions in aerospace environments.Additionally,these methods often assume a single-type uncer-tainty in the manufacturing process,leading to significant deviations between the analysis results and actual measurement results.To address these issues,this study proposes an efficient time-dependent reliability analysis method based on the HL-RF algorithm,considering a hybrid of prob-abilistic and interval uncertainty that accounts for degradation and environmental conditions.The proposed method is applied to the reliability analysis of actual aerospace electromagnetic relay products and compared with traditional methods,demonstrating significant advantages.The pro-posed method has been applied to the time-dependent reliability analysis of actual aerospace elec-tromagnetic relay products under different environmental conditions.The analysis results exhibit an error margin within 5.12％compared to actual measurement results.Compared to analysis methods solely based on probabilistic uncertainty quantification or interval uncertainty quantifica-tion,this method reduces the analysis error by 52％and 67％respectively.When compared to two other state-of-the-art methods that integrate probabilistic and interval uncertainty quantification,the error reduction is 23％.These demonstrate the superiority of the proposed method and validates its effectiveness.The presented approach has the potential to be extended for reliability analysis in other aerospace electromechanical systems.
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