基于ARMA模型的水下爆炸冲击谱预测

针对舰船设备抗冲击设计冲击环境预测难的问题，提出了利用自回归滑动平均模型（ARMA模型）预测水下爆炸冲击响应谱的方法，并引入遗传算法优化ARMA模型阶数。理论介绍了舰船设备水下爆炸冲击谱模型及ARMA模型。建模所需样本数据通过对有限元软件仿真输出的冲击响应信号进行去趋势化和平稳化处理获得，根据该样本数据的自相关函数和偏自相关函数统计特性分析，验证了ARMA建模的可行性。在此基础上，利用遗传算法优化后的ARMA模型，对水下爆炸冲击响应信号进行预测，并通过分析预测误差特性评估预测效果。研究结果表明，基于遗传算法优化的ARMA模型可以很好的预测水下爆炸冲击响应信号，从而为舰船设备抗冲击设计提供帮助。

Prediction of Shock Response Spectrum of Underwater Explosion Based on ARMA Model

An auto-regressive and moving average (ARMA) model is present to predict the underwater explosion shock environment for ship equipments. And genetic algorithm (GA) is used to optimize the determining ARMA orders. Spectrum model of underwater explosion shock response and ARMA model are theoretically analyzed. Sample data required for modeling is got from simulation results of explosion shock signal using finite element analysis software. And it is done by the trend of peace and stabilization treatment. Also feasibility of the ARMA model is proved by statistical characteristics of autocorrelation function and partial autocorrelation function based on the analysis of sample data. Then explosion shock spectrum is predicted by the ARMA model optimized by GA and its error characteristics are evaluated to judge effects of the method. Results show that it can get good performance to predict shock response spectrum using ARMA model optimized by GA. Thus help to design of shipboard equipment shock resistance.