Abstract: Aiming at the problem of propellant storage life prediction, this paper researched on the storage reliability of solid rocket motor, the aging performance of propellants, and structural integrity of grain. From those aspects, the GM-RBF neural network model, forecast model under mutative temperature and the accelerated aging test as well as structural integrity analysis method were proposed to estimate propellant storage life. The life prediction system was designed and developed. Through experimental data and simulation analyses, it is concluded that the life prediction range of SRM is between 10.5to 13.2years. Experimental and numerical results have shown that this forecasting method can avoid the limitation of single algorithm, and raise the forecasting precision.Meanwhile, the system can be widely used.

Key words: Solid rocket motor; Storage life; Prediction; Propellant

摘要： 针对固体火箭发动机装药贮存寿命预估的难题,开展了固体火箭发动机贮存可靠性、装药老化性能、药柱结构完整性分析等几个方面的研究,建立了GM-RBF网络模型、基于修正Arrhenius的交变温度预测模型、基于加速老化和结构完整性分析的装药贮存寿命预估模型,从不同角度来对装药贮存寿命进行组合预测。在此基础上,设计和开发了预测系统,通过实验数据和仿真分析,得到实例的装药贮存寿命区间为10.5~13.2y。研究表明:这种组合预测的方法避免了单一算法的局限性,提高了预测精度 。 

关键词: 固体火箭发动机;贮存寿命; 预测; 装药 