航天器环境工程2025，Vol.42Issue(5)：528-536,9.DOI:10.12126/see.2025057
融合TSO-GPR模型的导电滑环确信可靠性建模与评估
Belief reliability modeling and evaluation of conductive slip rings using an integrated TSO-GPR model
摘要
Abstract
The reliability of conductive slip rings,which are key components of the solar array drive assembly(SADA),is critical to the satellite's service life.Traditional analytical models struggle to characterize the complex nonlinear relationship between slip-ring wear and reliability.To address this issue,an artificial intelligence model integrating Tuna Swarm Optimization and Gaussian Process Regression(TSO-GPR)was proposed and trained using ground wear test data.An interdisciplinary equation was established to map the wear rate to the reed pressure and the hardness of the brush block material,and a belief reliability model was subsequently developed to account for uncertainties from multiple parameters.Validation results indicated that the TSO-GPR model reduced the root mean square error(RMSE)and mean absolute error(MAE)by approximately two orders of magnitude compared to the conventional GPR model,demonstrating significantly improved predictive accuracy and generalization capability for conductive slip-ring life prediction.Furthermore,sensitivity analysis revealed that the hardness of the brush block material had a greater influence on reliability than the reed pressure.These findings provide a useful reference for the design of high-reliability conductive slip rings.关键词
导电滑环/磨损/金枪鱼群优化-高斯过程回归模型/确信可靠性/敏感性分析Key words
conductive slip ring/wear/Tuna Swarm Optimization and Gaussian Process Regression(TSO-GPR)model/belief reliability/sensitivity analysis分类
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何贝琛,李晓阳,王晶,黄首清,张淑敏,王浩,吴冰林,康锐..融合TSO-GPR模型的导电滑环确信可靠性建模与评估[J].航天器环境工程,2025,42(5):528-536,9.基金项目
国家国防科工局技术基础科研项目(编号:JSZL2023203A003) （编号:JSZL2023203A003）
