基于数据驱动多尺度表征爆破信号特征提取研究

Research on Feature Extraction of Blasting Signals based on Data Driven Multi-Scale Representation

摘要

为消除爆破振动信号中噪声对信号特征提取的影响,利用变分模式分解(Variational mode decomposition,VMD)算法和Cramér von Mises(CVM)统计量,提出了一种基于数据驱动的爆破信号去噪方法,该方法使用统计距离的CVM度量来选择主要噪声模态,对其余模态局部使用CVM统计量来评估模态与估计噪声分布的关系,更接近噪声分布的模态被舍弃,从而获得更为真实的信号波动特性并进一步对消噪信号的时频分布、瞬时能量及边际能量分布进行了精细化特征提取。结果表明:CVM-VMD方法具有优越的数学和理论框架,使其对噪声和模态混叠具有很强的鲁棒性,使其在爆破信号去噪方面具有独特的优势。爆破信号时频谱表现出能量分布不均匀性、低频成分主导性和高频成分衰减性的显著特征。瞬时能量谱能够直观地展示信号能量在时域的实际变化情况,边际能量谱能够更准确地反映信号能量随频率的实际波动变化,为研究爆破机理和建筑物的受振影响评估提供了重要数据支持。

Abstract

To eliminate the influence of noise in blasting vibration signals on signal feature extraction, a data-driven blasting signal denoising method is proposed using Variational mode decomposition (VMD) algorithm and Cramér-von misse (CVM) statistic.This method uses the CVM metric of statistical distance to select the main noise modes, and locally uses the CVM statistic on the remaining modes to test the relationship between the modes and the estimated noise distribution. Modes closer to the noise distribution are discarded to obtain more realistic signal fluctuation characteristics. Subsequently, refined feature extraction is performed on time-frequency distribution, instantaneous energy, and marginal energy distribution of the denoised signal. The results indicate that the CVM-VMD method has superior mathematical and theoretical frameworks, making it highly robust to noise and mode mixing, and has unique advantages in blasting signals denoising. The time-frequency spectrum of blasting signals exhibits significant characteristics of uneven energy distribution, dominance of low-frequency components, and attenuation of high-frequency components. The instantaneous energy spectrum can intuitively display the changes in signal energy at different time points, while the marginal energy spectrum can more accurately reflect the fluctuation of signal energy with actual frequency, which provides important data support for studying blasting mechanisms and evaluating the vibration effects on buildings.

关键词

爆破信号 / 信号去噪 / CVM-VMD / 时频分析 / 能量分布

Key words

Blasting signals / Signals denoising / Cramér-von misse-variational mode decomposition / Time-frequency analysis / Energy distribution

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基金资助

国家级大学生创新训练项目“新型化能瞬态气胀致裂破岩振动效应与控制技术研究”(202511311015)

福建省自然科学基金联合资助项目计划“新型破岩气体发生器振动效应与灾害评估研究”(2024J01905)

鞍钢矿业爆破有限公司企业委托项目“基于可视化的台阶微差控制爆破技术研究”(HX20250204)