运载火箭飞行振动信号盲源分离方法

针对振动信号在火箭复杂结构传播过程中产生强卷积效应导致振动源信号提取精度低的难题，研究了一种基于卷积盲源分离的火箭振动信号自适应提取方法。该方法基于振动源之间的独立性，建立了四阶统计量的目标函数，并采用随机梯度法实现了参数的自适应更新，优化建立火箭复杂结构系统的逆滤波器结构，进而得到原始的振动源信号。通过对某运载火箭发动机的高频振动数据进行分析，结果表明：相较于线性自适应盲源分离方法和非线性自适应盲源分离方法，卷积自适应盲源分离由于考虑了实际中的卷积效应和欠定情况，分离结果中能够明显找到与涡轮转动和燃烧对应的频率以及一些宽频激励，验证了提出方法的有效性。

Blind Source Separation Method for Flight Vibration Signal of Launch Vehicle

To solve the problem of low precision of vibration source signals extraction caused by the strong convolution effect of vibration signals in the process of rocket shell propagation, an adaptive extraction method of rocket vibration signals based on convolution blind source separation is studied. Based on the independence among the vibration sources, the method establishes the objective function of the fourth order statistics, and uses the random gradient method to realize the adaptive updating of parameters. The inverse filter structure of the rocket shell system is optimized to obtain the original vibration source signal. By analyzing the high frequency vibration data of a carrier rocket engine, the results show that, compared with the linear adaptive blind source separation method and the nonlinear adaptive blind source separation method, the convolution adaptive blind source separation method can obviously find the frequency corresponding to turbine rotation and combustion, as well as some broadband excitation, due to considering the convolution effect and underdetermined conditions in practice, which verifies the effectiveness of the proposed method.