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Time-frequency Analysis of Shock Wave Signals Based on VMD Variational Mode Decomposition
Received date: 2020-11-06
Online published: 2025-02-21
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.
Key words: VMD; time-frequency analysis; explosive shock wave; signal processing
GUO Jiahui , GAO Yixuan , LIU Changwei , ZU Xudong . Time-frequency Analysis of Shock Wave Signals Based on VMD Variational Mode Decomposition[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2022 , 42(1) : 118 -122 . DOI: 10.15892/j.cnki.djzdxb.2022.01.022
| [1] |
李丽萍, 孔德仁, 苏建军, 等. 基于能量谱的爆炸冲击波毁伤特性研究[J]. 振动与冲击, 2015, 34(21):71-75.
|
| [2] |
马伦, 康建设, 孟妍, 等. 基于Morlet小波变换的滚动轴承早期故障特征提取研究[J]. 仪器仪表学报, 2013, 34(4):920-926.
|
| [3] |
程皓, 张志杰, 张浩, 等. 改进EMD算法在爆炸冲击波后处理中的应用[J]. 电子测量技术, 2018, 41(23):78-81.
|
| [4] |
黄沁元, 谢罗峰, 殷国富, 等. 基于变分模态分解和天牛须搜索的磁瓦内部缺陷声振检测[J]. 振动与冲击, 2020, 39(17):124-133.
|
| [5] |
许子非, 岳敏楠, 李春. 优化递归变分模态分解及其在非线性信号处理中的应用[J]. 物理学报, 2019, 68(23):292-305.
|
| [6] |
赵昕海, 张术臣, 李志深, 等. 基于VMD的故障特征信号提取方法[J]. 振动、测试与诊断, 2018, 38(1):11-19.
|
| [7] |
刘建昌, 权贺, 于霞, 等. 基于参数优化VMD和样本熵的滚动轴承故障诊断[J]. 自动化学报, 2019, 12(12):1-12.
|
| [8] |
唐贵基, 王晓龙. 参数优化变分模态分解方法在滚动轴承早期故障诊断中的应用[J]. 西安交通大学学报, 2015, 49(5):73-81.
|
| [9] |
贾贝, 凌天龙, 侯仕军, 等. 变分模态分解在爆破信号趋势项去除中的应用[J]. 爆炸与冲击, 2020, 40(4):123-131.
|
| [10] |
马洪斌, 佟庆彬, 张亚男. 优化参数的变分模态分解在滚动轴承故障诊断中的应用[J]. 中国机械工程, 2018, 29(4):390-397.
|
| [11] |
吴文轩, 王志坚, 张纪平, 等. 基于峭度的VMD分解中k值的确定方法研究[J]. 机械传动, 2018, 42(8):153-157.
|
| [12] |
王晓龙. 基于振动信号处理的滚动轴承故障诊断方法研究[D]. 北京: 华北电力大学, 2017.
|
| [13] |
张莹, 殷红, 彭珍瑞. 基于改进SVD及参数优化VMD的轴承故障诊断[J]. 噪声与振动控制, 2020, 40(1):51-58.
|
| [14] |
|
/
| 〈 |
|
〉 |