|Table of Contents|

Energy distribution and prediction of rock vibration generated in blasting excavation of a deep tunnel(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2023年1期
Page:
62-71
Research Field:
隧道工程
Publishing date:

Info

Title:
Energy distribution and prediction of rock vibration generated in blasting excavation of a deep tunnel
Author(s):
TU Ying1;  YAN Yu-song1;  YANG Jian-hua1;  ZHANG Wei-peng2;  LIU Da3
(1. School of Infrastructure Engineering, Nanchang University, Nanchang 330031, Jiangxi, China; 2. China Railway Water Conservancy & Hydropower Planning and Design Group Co., Ltd, Nanchang 330029, Jiangxi, China; 3. Jiangxi Academy of Water Science and Engineering, Nanchang 330029, Jiangxi, China)
Keywords:
tunnel engineering;  blasting excavation;  rock vibration;  wavelet packet;  energy distribution;  vibration prediction
PACS:
U455
DOI:
10.19721/j.cnki.1671-8879.2023.01.007
Abstract:
During blasting excavation of deep tunnels, the rapid in-situ stress release occurring on blast-created free surfaces was an important factor that produces vibration in surrounding rock masses. In order to understand the characteristics of the rock vibration caused by the combined effects of blast loading and rapid stress release, the rock vibration monitored in the blasting excavation of the upper middle pilot tunnel in Jinping Underground Laboratory was investigated. The monitored vibration signals were first separated into blasting vibration and stress release-induced vibration by using the variational mode decomposition(VMD)method. The wavelet packet method was then employed to study the energy distribution characteristics, and their influencing factors for the respective blasting vibration and stress release-induced vibration. A model was finally developed to predict the rock vibration caused by the combined effects of blast loading and rapid stress release. The results show that the energy of the blasting vibration is mainly distributed in the frequency band of 200 to 300 Hz. While the energy of the stress release-induced vibration is mainly concentrated in 0 to 150 Hz. The frequency of the stress release-induced vibration is significantly lower than that of the blasting vibration. As the travel distance increases, the ratio of the energy in lower frequencies to the total energy increases significantly, whether for the blasting vibration or the stress release-induced vibration. The energy distribution of the blasting vibration is also affected by the amount of charge filled in the blastholes. With an increase in the charge weight, the proportion of the low-frequency energy increases. However, the amount of charge has no effect on the energy distribution of the stress release-induced vibration. The energy distribution of the stress release-induced vibration is also independent of the level of the initial in-situ stress on the blast-created free surfaces, but is related to the duration of the stress release and the size of the free surfaces. A back propagation neural network based on the genetic algorithm(GA-BPNN)model is developed to predict the peak particle velocity(PPV), and center frequency of the rock vibration caused by the combined effects of blast loading and rapid stress release. In the GA-BPNN prediction model, seven physical quantities, including charge weight per delay, charge weight per blasthole, number of blastholes, blasthole spacing, blasting-to-monitoring distance, initial normal stress on the free surfaces and stress release duration, are considered as input parameters. The relative errors of the predicted PPV and center frequency are 10.4% and 3.2%, respectively.1 tab, 9 figs, 26 refs.

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Last Update: 2023-01-30