关键词: 气爆破岩, 振动信号, 优化分解, 相关特征, 递归图, 灰狼优化-变分模态分解(GWO-VMD)

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)