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基于VMD变分模态分解的冲击波信号时频分析 被引量:3

Time-frequency Analysis of Shock Wave Signals Based on VMD Variational Mode Decomposition
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摘要 冲击波信号时频分析是研究结构件抗爆特性和振动特性的基础。为了研究变分模态分解方法(VMD)在分析冲击波信号时的适用性,通过爆炸试验,测得炸药在不同爆心距的爆炸冲击波超压时程曲线。然后依据爆炸冲击波信号的时频特征讨论了算法中分解级数和惩罚因子的取值方法。通过VMD方法对爆炸冲击波信号进行分解,给出了分解后各分量的时域和频域信号的波形及分布规律。结果表明,在惩罚因子取0.15~0.5倍信号长度,且分解级数取幅频曲线分段数时,分解后信号的时域保真度和频域分辨率较好,爆炸冲击波能量主要集中在中低频部分和优势子频带部分,而在高频部分的能量分布相对较少,具有幅值较小,频带较宽的特点。 Time-frequency analysis of shock wave signals is the basis of studying the anti-knock and vibration characteristics of structural components.In order to study the applicability of the variational mode decomposition method(VMD)in the analysis of shock wave signals,the time history curves of the blast wave overpressure at different detonation center distances of explosives were measured by explosion tests.Then according to the time-frequency characteristics of blast wave signal,the decomposition order and the value of penalty factor in the algorithm are discussed.The blast wave signal is decomposed by VMD method,and the waveform and distribution rule of each component in time domain and frequency domain after the shock wave signal decomposition are given.The results show that the time domain fidelity and frequency domain resolution of the decomposed signal are good when the penalty factor is 0.15~0.5 times of the signal length and the number of segments of the amplitude-frequency curve is taken as the decomposition stage.Among them,the energy of blast wave is mainly concentrated in the middle and low frequency part and the dominant sub-frequency band part,while the energy distribution in the high frequency part is relatively small,which has the characteristics of small amplitude and wide frequency band.
作者 郭佳辉 高一轩 刘昌伟 祖旭东 GUO Jiahui;GAO Yixuan;LIU Changwei;ZU Xudong(School of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China)
出处 《弹箭与制导学报》 北大核心 2022年第1期118-122,共5页 Journal of Projectiles,Rockets,Missiles and Guidance
关键词 VMD 时频分析 爆炸冲击波 信号处理 VMD time-frequency analysis explosive shock wave signal processing
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