侵彻过载信号自适应变分模态分解时频分析方法

Penetration Overload Signal Time Frequency Analysis Method Based on Adaptive OVMD

传统过载信号时频分析方法广泛应用于超高速侵彻引信层间粘连机理研究和信号处理方法优化中,但模态混叠效应已成为其应用时的瓶颈。针对该问题,提出一种基于自适应优化变分模态分解(OVMD)的侵彻过载信号时频分析方法。考虑到侵彻过载信号频率成分复杂且具有的非平稳性、随机性特点,该方法以模态的混叠效应和稀疏性作为信号的分解约束,采用非支配排序遗传算法(NSGA-II)搜索获取变分模态分解算法的分解个数和二次惩罚因子,再基于参数优化的变分模型,确定各模态函数的中心频率和带宽,完成过载信号各频率成分的自适应分解。通过对实测侵彻过载信号分析可见,相比于通用经验模态分解算法,该方法可以有效抑制模态混叠现象,且在时域和频域上均具有更好的分辨率,能为引信系统的信号处理、仿真模型验证、结构设计提供有效信息支撑。

The traditional time-frequency analysis method for overload signals is widely used in the study of the multi-level target adhesion mechanism and the optimization of signal processing methods for high-speed penetration fuses,but the modal aliasing effect has become a bottleneck in its application.To address this issue,this paper proposed a time-frequency analysis method for penetration overload signals based on adaptive optimal variational mode decomposition(OVMD).Considering that the frequency components of the penetration overload signal were complex and had the characteristics of non-stationarity and randomness,this method took the aliasing effect and sparsity of modes as the decomposition constraints of the signal and adopted the non-dominated sorting genetic algorithm(NSGA-II)to search for and obtain the number of decompositions and the quadratic penalty factors of the variational mode decomposition algorithm.Then,based on the parameter-optimized variational model,the center frequency and bandwidth of each modal function were determined,and the different frequency components of the overload signal were adaptively decomposed.Finally,through the analysis results of the measured penetration overload signal,it was observed that compared with the general empirical mode decomposition algorithm,this method could effectively suppress the modal aliasing phenomenon and had better resolution in both the time and frequency domains.It could provide effective information support for signal processing,simulation model verification,and structural design of the fuze system.