Optimization decomposition and related feature analysis of rock vibration signals in gas blasting

doi:10.16265/j.cnki.issn1003-3033.2025.05.1493

Abstract

Abstract:

In order to solve the problem of difficulty in determining the number of modes and quadratic penalty factors in the process of variational mode decomposition, a GWO-VMD algorithm was proposed. Based on the Longlong Tunnel gas explosion method construction, an integrated acquisition module was used to collect vibration signals during the rock-breaking process. The phase space reconstruction recursive graph (RP) similarity model was used to accurately distinguish the GWO-VMD principal components of the signals. The real signal with interference removed was reconstructed, revealing the distribution characteristics of the energy of the gas explosion signal in the time-frequency domain, and qua.pngying the accuracy error of the digital electronic detonator. The results show that compared with traditional variational mode algorithms, the GWO-VMD algorithm has significant advantages in improving the signal-to-noise ratio and adaptive feature extraction of gas explosion signals, and has strong time-varying frequency tracking performance. It can accurately ide.pngy the detonation accuracy of digital detonators and effectively ide.pngy the related of tunnel-blasting detonator disaster sources.

Key words: gas rock breaking, vibration signal, optimize decomposition, related features, recurrence plot, grey wolf optimizer-variational mode decomposition(GWO-VMD)

CLC Number:

X932爆炸安全与防火、防爆

FU Xiaoqiang, DAI Liangyu, YU Jin, SHAO Yiqiang. Optimization decomposition and related feature analysis of rock vibration signals in gas blasting[J]. China Safety Science Journal, 2025, 35(5): 64-72.

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序号	孔位孔名	孔数	单支药量/kg	单孔药量/kg	炮孔角度/(°)	炮孔深度/m	单段药量/ kg	延期时间/ ms	药径/ mm
1	掏槽孔①	6	1.8	3.6	65	2.97	21.6	0	75
2	掏槽孔②	6	1.8	3.6	75	3.00	21.6	50
3	辅助孔①	9	1.8	1.8	90	2.50	16.2	100
4	辅助孔②	11	1.8	1.8	90	2.50	19.8	200
5	辅助孔③	14	1.8	1.8	90	2.50	25.2	300
6	辅助孔④	17	0.6	1.8	90	2.50	30.6	400
7	周边孔	27	0.6	0.6	90	2.50	16.2	500	32
8	底孔	11	1.8	1.8	90	2.50	19.8	600	75
合计		101	—				171	—	—

分量	IMF1	IMF2	IMF3	IMF4	IMF5
相似度/%	95.38	83.54	80.27	74.91	56.13
分量	IMF6	IMF7	IMF8	Res	—
相似度/%	6.38	5.25	4.33	3.72	—