水下爆炸诱发冲击振动的自适应模态分解方法

龙毅扬; 朱炜; 闻俊; 贾曦雨; 马峰

doi:10.11993/j.issn.2096-3920.2026-0004

水下爆炸诱发冲击振动的自适应模态分解方法

doi: 10.11993/j.issn.2096-3920.2026-0004

北京理工大学爆炸科学与安全防护全国重点实验室, 北京, 100081

基金项目: 国家自然科学基金重点项目(12472365); 爆炸科学与安全防护全国重点实验室自主课题重点项目(ZDKT24-01).

详细信息

作者简介:
龙毅扬(2001-), 男, 在读硕士, 主要研究方向为水下爆炸与结构冲击响应

中图分类号: TJ630; U663
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- 被引次数: 0
出版历程
- 收稿日期: 2026-01-07
- 修回日期: 2026-02-20
- 录用日期: 2026-03-04
- 网络出版日期: 2026-07-21

Adaptive Modal Decomposition Method for Underwater Explosion-Induced Shock Vibrations

State Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, China

摘要

摘要: 水下爆炸诱发的结构冲击振动信号具有强非平稳和宽频叠加特征, 传统模态分解方法易产生模态混叠与能量泄露, 难以实现稳定的频域分离。针对上述问题, 提出了一种水下爆炸冲击振动的自适应模态分解方法(AMD)。该方法基于频域参数化建模, 利用具有局部支持和可调尺度特性的基函数表示响应频谱, 并通过中心、带宽与幅值参数的协同优化及剪枝约束, 实现主要频率成分的自适应提取与模态重构。以水下爆炸板架结构数值仿真数据为例, 将AMD与经验模态分解(EMD)、变分模态分解(VMD)和经验小波变换(EWT)方法进行对比分析。结果表明, AMD实现了近似无损重构, 其模态间最大互相关系数约为17.7%, 频谱重叠率均值为2.7%, 显著低于对比方法, 可为水下爆炸冲击振动信号分析提供有效工具。
- 水下爆炸 /
- 冲击振动 /
- 自适应模态分解 /
- 频谱重叠率
Abstract: Structural shock–vibration signals induced by underwater explosions exhibit strong non-stationarity and broadband superposition. Conventional modal decomposition methods are prone to mode mixing and energy leakage, making it difficult to achieve stable frequency-band separation. To address these issues, an adaptive modal decomposition method for underwater-explosion-induced shock vibration, termed adaptive modal decomposition (AMD), is proposed. The method is built on frequency-domain parametric modeling, where the response spectrum is represented by basis functions with local support and adjustable scale, and the dominant frequency components are adaptively extracted and reconstructed via the joint optimization of center frequency, bandwidth, and amplitude parameters together with pruning constraints. A numerical simulation of an underwater-explosion stiffened-plate structure is used as an example, and AMD is systematically compared with empirical mode decomposition(EMD), empirical mode decomposition(VMD) and empirical mode decomposition(EWT). The results indicate that AMD achieves near-lossless reconstruction, with a maximum inter-modal cross-correlation coefficient of approximately 17.7% and an average spectral overlap ratio of 2.7%, both significantly lower than those of the compared methods, demonstrating its effectiveness for shock-vibration signal analysis under underwater explosion.
- underwater explosion /
- shock vibration /
- adaptive modal decomposition /
- spectral overlap ratio

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图 1 AMD网络架构

Figure 1. Overall framework of the AMD method

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图 2 板架结构模型及水下爆炸工况示意图

Figure 2. Plate frame structure model and schematic diagram of underwater explosion conditions

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图 3 冲击振动响应时程对比

Figure 3. Time history comparison of shock vibration response

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图 4 AMD方法频域核函数自适应优化过程

Figure 4. Adaptive optimization process of amd method in frequency domain kernel function

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图 5 不同分解方法模态分量时域波形对比

Figure 5. Comparison of time domain waveforms of modal components by different decomposition methods

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图 6 不同分解方法模态分量幅频特性对比

Figure 6. Comparison of amplitude frequency characteristics of modal components by different decomposition methods

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图 7 不同分解方法模态间互相关性统计指标对比

Figure 7. Comparison of statistical indexes of modal cross correlation between different decomposition methods

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图 8 不同分解方法模态OVL统计对比

Figure 8. Statistical comparison of modal OVL with different decomposition methods

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表 1 不同分解方法的信号重构误差对比

Table 1. Comparison of signal reconstruction errors of different decomposition methods

方法模态数 RE RMSE

AMD 6 1.4×10⁻⁷ 2.2×10⁻³
EMD 10 5.9×10⁻³ 91.7
VMD 6 3.6×10⁻¹ 570.1
EWT 10 5.4×10⁻³ 118.0

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