基于多测点数据的火箭飞行模态参数识别方法

Rocket flight modal identification method based on data of multi-measure points

目前基于多个测点数据的火箭飞行模态参数识别,一般是通过每个测点数据单独处理的方式来进行的,在工程应用中可能存在识别精度不足、计算量偏大的问题。针对该问题,提出了整体ARMA模型时序分析法,同时采用全部测点测试数据,对火箭的飞行过程中的固有频率和阻尼比进行了计算和识别。通过某火箭飞行试验实测的3个测点的振动数据,经过重采样、滤波、互相关等处理后,采用以上方法,整体计算并识别了火箭结构横向模态参数并进行了分析。结果表明,该方法能够辨识出火箭结构的横向模态参数,而且相较传统方法可有效减小计算量,且具有每阶模态对应的固有频率和阻尼比唯一的特点。

At present,the flight modal parameters identification of rocket based on multi-measure points was commonly conducted by each point alone,which had disadvantages including low identification precision and a large amount of calculation.Therefore,the integral ARMA（ auto regressive moving average） model time sequence analysis method was proposed to use all the measure data points to calculate and identify the natural frequencies and damping ratios of rocket during flight. A rocket＇s three-channels flight test data was used. After re-sample,filter and cross functioning process,ARMA model time sequence analysis method was used to calculate and identify integrally the rocket structure modal parameters by full test data.The results show that the method can identify the rocket lateral modal parameters efficiently. Moreover,it could reduce the amount of calculation,and it has a characteristic that each modal corresponded with exclusive natural frequency and damping ratio.