A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices

Coal bump, a common dynamic disaster in mining of deep coal resources, its assessing and predicting is an important component in safety management. This paper presents a model to assess and predict coal bump risk based on multiparameter indices. A new energy accumulation index S was proposed by cons...

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Main Authors: Tao Luo, Gangwei Fan, Shizhong Zhang, Shang Ren, Yibo Fan, Ruiliang Shen
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Geofluids
Online Access:http://dx.doi.org/10.1155/2022/2090809
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author Tao Luo
Gangwei Fan
Shizhong Zhang
Shang Ren
Yibo Fan
Ruiliang Shen
author_facet Tao Luo
Gangwei Fan
Shizhong Zhang
Shang Ren
Yibo Fan
Ruiliang Shen
author_sort Tao Luo
collection DOAJ
description Coal bump, a common dynamic disaster in mining of deep coal resources, its assessing and predicting is an important component in safety management. This paper presents a model to assess and predict coal bump risk based on multiparameter indices. A new energy accumulation index S was proposed by considering acoustic emission and electromagnetic emission signal characteristics in mine shocks. Combined with indices E (energy of microseisms) and N (frequency of microseisms) of microseismic monitoring, a static and dynamic coal bump risk assessment and prediction model was established. We studied coal bump events that occurred during extraction in 311305 working face of Bayangale coal mine in Inner Mongolia, China. We obtained the acoustic emission and electromagnetic emission signal distribution and change law, using principal component analysis method and density ellipse to establish the index S. A typical precursory of coal bumps is that AE and EME strength has obvious fluctuation period of 3-4 days, index S showing an obvious decreasing trend, while the time-series curve of the microseismic energy is relatively stable, and the vibration frequency curve has a significant upward trend. After predict the potential coal bump risk and its area of occurrence, large diameter drilling (Φ150 mm) on-site was used to relief pressure concertation in coal seam and roof. The results demonstrate that this model based on multiparameter indices is capable of quantitatively prewarning rock burst risk.
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issn 1468-8123
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publishDate 2022-01-01
publisher Wiley
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series Geofluids
spelling doaj-art-8b8ee27e76f74a5cb1d92c84bb193d6e2025-08-20T03:37:40ZengWileyGeofluids1468-81232022-01-01202210.1155/2022/2090809A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter IndicesTao Luo0Gangwei Fan1Shizhong Zhang2Shang Ren3Yibo Fan4Ruiliang Shen5School of MinesSchool of MinesSchool of MinesSchool of MinesSchool of MinesSchool of MinesCoal bump, a common dynamic disaster in mining of deep coal resources, its assessing and predicting is an important component in safety management. This paper presents a model to assess and predict coal bump risk based on multiparameter indices. A new energy accumulation index S was proposed by considering acoustic emission and electromagnetic emission signal characteristics in mine shocks. Combined with indices E (energy of microseisms) and N (frequency of microseisms) of microseismic monitoring, a static and dynamic coal bump risk assessment and prediction model was established. We studied coal bump events that occurred during extraction in 311305 working face of Bayangale coal mine in Inner Mongolia, China. We obtained the acoustic emission and electromagnetic emission signal distribution and change law, using principal component analysis method and density ellipse to establish the index S. A typical precursory of coal bumps is that AE and EME strength has obvious fluctuation period of 3-4 days, index S showing an obvious decreasing trend, while the time-series curve of the microseismic energy is relatively stable, and the vibration frequency curve has a significant upward trend. After predict the potential coal bump risk and its area of occurrence, large diameter drilling (Φ150 mm) on-site was used to relief pressure concertation in coal seam and roof. The results demonstrate that this model based on multiparameter indices is capable of quantitatively prewarning rock burst risk.http://dx.doi.org/10.1155/2022/2090809
spellingShingle Tao Luo
Gangwei Fan
Shizhong Zhang
Shang Ren
Yibo Fan
Ruiliang Shen
A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices
Geofluids
title A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices
title_full A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices
title_fullStr A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices
title_full_unstemmed A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices
title_short A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices
title_sort coal bump risk assessment and prediction model based on multiparameter indices
url http://dx.doi.org/10.1155/2022/2090809
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