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Research Article | Open Access

Microseismic source location based on improved artificial bee colony algorithm: Performance analysis and case study

Peng Zhang1Nuwen Xu1( )Peiwei Xiao1,2Tao Zhao3Furong Gao2Xinchao Ding4Biao Li5( )
State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China
CHN Energy Jinsha River Xulong Hydropower Co., Ltd., Tibetan Autonomous Prefecture of Garzê 627950, China
Department of Civil and Environmental Engineering, Brunel University, London UB8 3PH, UK
PowerChina Northwest Engineering Co., Ltd., Xi’an 710065, China
School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
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Abstract

Highly accurate microseismic (MS) localization is the basis for rock damage assessment and disaster warning. The engineering background noise mixed in the MS signal (s(ε)) seriously affects the subsequent analysis of the MS signal. A noise reduction method of singular spectral analysis–complementary ensemble empirical mode decomposition–wavelet threshold (SSA–CEEMD–WT) is proposed. The CEEMD, CEEMD–WT, and proposed methods are used for denoising the noisy Ricker wavelet. The signal-to-noise ratio (SNR) of the denoised signal (xde(ε)) by the proposed method is 56.77% and 37.88% higher than those of CEEMD and CEEMD–WT methods, respectively. Moreover, an adaptive artificial bee colony (ABC) algorithm is applied for MS source (O(h0, y0, z0)) location. The time to quantile difference is introduced as the objective function. The blast positioning test results prove that the proposed method improves the positioning accuracy of particle swarm optimization (PSO) algorithm and simulated annealing PSO (SA-PSO) algorithm by 44.12% and 47.64%, respectively. The MS positions of underground caverns reveal that the calculated clusters of MS events using the adaptive ABC algorithm are more concentrated at the structural plane and appearance deformation failure location and in good agreement with field survey and routine monitoring data.

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Journal of Intelligent Construction
Article number: 9180016
Cite this article:
Zhang P, Xu N, Xiao P, et al. Microseismic source location based on improved artificial bee colony algorithm: Performance analysis and case study. Journal of Intelligent Construction, 2023, 1(3): 9180016. https://doi.org/10.26599/JIC.2023.9180016

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Received: 28 June 2023
Revised: 30 July 2023
Accepted: 01 August 2023
Published: 13 September 2023
© The Author(s) 2023. Published by Tsinghua University Press.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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