RESEARCH ARTICLE
Optimal Design of Micro-Seismic Monitoring Array and Seismic Source Location Estimation for Rock Slope
Nuwen Xu*, 1, Chun-an Tang2, Hong Li1, Sihao Wu3
Article Information
Identifiers and Pagination:
Year: 2011Volume: 5
First Page: 36
Last Page: 45
Publisher ID: TOCIEJ-5-36
DOI: 10.2174/1874149501105010036
Article History:
Received Date: 7/7/2010Revision Received Date: 21/11/2010
Acceptance Date: 4/1/2011
Electronic publication date: 29/4/2011
Collection year: 2011
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
For the purpose of getting a better understanding on failure mechanism of rock fracturing due to construction perturbation inside the rock slope at the right bank of Dagangshan Hydropower Station, southwest of China, a highprecision microseismic monitoring system was installed and source location data has preliminarily been investigated. The optimal design of microseismic monitoring network, especially the sensor array was investigate based on P method and Powell algorithm. The positioning accuracy of the system has been adjusted according to the artificial fixed blasting tests. The testing results show that the error in localizing microseismic source is less than 10 m within the scope of the sensor array, indicating that the positioning accuracy for the monitoring system deployed at the right bank slope is high. Signals from 255 microseismic events with moment magnitude ranging from -1.8 to -0.4 were recorded during the 2-month monitoring period. The cluster distribution of microseismic events such as the concentration of microseismicity inside the drainage tunnel at 1081 m level can directly reflect the construction progress. The present study has significantly improved the understanding of the characteristics of the failure associated with excavation inside the rock slope. It will greatly benefit the prediction on potential sliding areas and support to prevent hazards during construction phases.
