六盘水师范学院学报2026，Vol.38Issue(3)：12-24,13.DOI:10.16595/j.1671-055X.2026.03.002
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
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)algo-rithm 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 be-tween 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-fre-quency spectrum of blasting signals exhibits significant characteristics of uneven energy distribution,domi-nance 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 ener-gy 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分类
矿业与冶金引用本文复制引用
黄嘉瑞,付晓强,闫大洋,苏洪,霍艺强..基于数据驱动多尺度表征爆破信号特征提取研究[J].六盘水师范学院学报,2026,38(3):12-24,13.基金项目
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) （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) （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). （HX20250204）
