Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals
Abstract Coal burst is one of the most frequent and destructive dynamic disasters encountered during underground mining engineering. However, the understanding of quantitative precursor characteristics of coal burst is still in its infancy, rendering it difficult to provide effective early warning o...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Geomechanics and Geophysics for Geo-Energy and Geo-Resources |
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| Online Access: | https://doi.org/10.1007/s40948-024-00924-0 |
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| _version_ | 1832594328647630848 |
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| author | Xiaoling Zhao Zhiyi Liao Xiufeng Zhang Cong Shen Jianbo Zhu |
| author_facet | Xiaoling Zhao Zhiyi Liao Xiufeng Zhang Cong Shen Jianbo Zhu |
| author_sort | Xiaoling Zhao |
| collection | DOAJ |
| description | Abstract Coal burst is one of the most frequent and destructive dynamic disasters encountered during underground mining engineering. However, the understanding of quantitative precursor characteristics of coal burst is still in its infancy, rendering it difficult to provide effective early warning of disaster. In this study, to quantitatively study precursor characteristics and warning signs of coal burst, the coal burst experiments were carried out on coal-rock combination with a crack. The acoustic emission (AE) technique was employed to quantitatively analyse the precursor information during coal burst process. Testing results indicated that coal burst process is classified into three stages based on evolution in AE energy, i.e., early incubation stage, late incubation stage and occurrence stage. The first significant increase in AE energy could be identified as the beginning of the late incubation stage of coal burst, accompanying by the phenomenon of macro-failure initiation. AE signals during the whole process could be classified as five types according to their dominant frequency and amplitude characteristics, i.e., HF-HA, LF-HA, EHF-LA, HF-LA and LF-LA respectively. The dramatic increase in number proportion of HF-HA and LF-HA signals is highly correlated with occurrence of coal burst. In addition, a comprehensive classification criterion for the coal burst prediction was proposed under a quantitative analysis of three AE parameters, i.e., first energy index (FEI), coal burst risk indicator based on AE energy (CRI E ) and frequency spectrum (CRI F−A ). The findings in this study could facilitate accurate coal burst prediction. |
| format | Article |
| id | doaj-art-36f84e906cc644548920fa7e657b9cd9 |
| institution | Kabale University |
| issn | 2363-8419 2363-8427 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Geomechanics and Geophysics for Geo-Energy and Geo-Resources |
| spelling | doaj-art-36f84e906cc644548920fa7e657b9cd92025-01-19T12:43:06ZengSpringerGeomechanics and Geophysics for Geo-Energy and Geo-Resources2363-84192363-84272025-01-0111112110.1007/s40948-024-00924-0Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signalsXiaoling Zhao0Zhiyi Liao1Xiufeng Zhang2Cong Shen3Jianbo Zhu4State Key Laboratory of Hydraulic Engineering Simulation and Safety, School of Civil Engineering, Tianjin UniversityInstitute of Rock Instability and Seismicity Research, Dalian University of TechnologyShandong Energy Group Co., LTDState Key Laboratory of Hydraulic Engineering Simulation and Safety, School of Civil Engineering, Tianjin UniversityGuangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization, Institute of Deep Earth Sciences and Green Energy, College of Civil and Transportation Engineering, Shenzhen UniversityAbstract Coal burst is one of the most frequent and destructive dynamic disasters encountered during underground mining engineering. However, the understanding of quantitative precursor characteristics of coal burst is still in its infancy, rendering it difficult to provide effective early warning of disaster. In this study, to quantitatively study precursor characteristics and warning signs of coal burst, the coal burst experiments were carried out on coal-rock combination with a crack. The acoustic emission (AE) technique was employed to quantitatively analyse the precursor information during coal burst process. Testing results indicated that coal burst process is classified into three stages based on evolution in AE energy, i.e., early incubation stage, late incubation stage and occurrence stage. The first significant increase in AE energy could be identified as the beginning of the late incubation stage of coal burst, accompanying by the phenomenon of macro-failure initiation. AE signals during the whole process could be classified as five types according to their dominant frequency and amplitude characteristics, i.e., HF-HA, LF-HA, EHF-LA, HF-LA and LF-LA respectively. The dramatic increase in number proportion of HF-HA and LF-HA signals is highly correlated with occurrence of coal burst. In addition, a comprehensive classification criterion for the coal burst prediction was proposed under a quantitative analysis of three AE parameters, i.e., first energy index (FEI), coal burst risk indicator based on AE energy (CRI E ) and frequency spectrum (CRI F−A ). The findings in this study could facilitate accurate coal burst prediction.https://doi.org/10.1007/s40948-024-00924-0Coal burstAcoustic emissionPrecursorEarly warning |
| spellingShingle | Xiaoling Zhao Zhiyi Liao Xiufeng Zhang Cong Shen Jianbo Zhu Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals Geomechanics and Geophysics for Geo-Energy and Geo-Resources Coal burst Acoustic emission Precursor Early warning |
| title | Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals |
| title_full | Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals |
| title_fullStr | Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals |
| title_full_unstemmed | Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals |
| title_short | Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals |
| title_sort | experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals |
| topic | Coal burst Acoustic emission Precursor Early warning |
| url | https://doi.org/10.1007/s40948-024-00924-0 |
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