A method to predict rockburst using temporal trend test and its application
Rockbursts have become a significant hazard in underground mining, underscoring the need for a robust early warning model to ensure safety management. This study presents a novel approach for rockburst prediction, integrating the Mann-Kendall trend test (MKT) and multi-indices fusion to enable real-...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Journal of Rock Mechanics and Geotechnical Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674775523002512 |
| _version_ | 1797262927847227392 |
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| author | Yarong Xue Zhenlei Li Dazhao Song Xueqiu He Honglei Wang Chao Zhou Jianqiang Chen Aleksei Sobolev |
| author_facet | Yarong Xue Zhenlei Li Dazhao Song Xueqiu He Honglei Wang Chao Zhou Jianqiang Chen Aleksei Sobolev |
| author_sort | Yarong Xue |
| collection | DOAJ |
| description | Rockbursts have become a significant hazard in underground mining, underscoring the need for a robust early warning model to ensure safety management. This study presents a novel approach for rockburst prediction, integrating the Mann-Kendall trend test (MKT) and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards. The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts. The MKT is then applied to analyze the real-time trend of each index, with adherence to rockburst characterization laws serving as the warning criterion. By employing a confusion matrix, the warning effectiveness of each index is assessed, enabling index preference determination. Ultimately, the integrated rockburst hazard index Q is derived through data fusion. The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q, surpassing the performance of any individual index. Moreover, the model's adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data, making it suitable for complex underground working environments. By providing an efficient and accurate basis for decision-making, the proposed model holds great potential for the prevention and control of rockbursts. It offers a valuable tool for enhancing safety measures in underground mining operations. |
| first_indexed | 2024-04-25T00:04:54Z |
| format | Article |
| id | doaj.art-7bd334c7b912476792d00128691f99d6 |
| institution | Directory Open Access Journal |
| issn | 1674-7755 |
| language | English |
| last_indexed | 2024-04-25T00:04:54Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Rock Mechanics and Geotechnical Engineering |
| spelling | doaj.art-7bd334c7b912476792d00128691f99d62024-03-14T06:14:17ZengElsevierJournal of Rock Mechanics and Geotechnical Engineering1674-77552024-03-01163909923A method to predict rockburst using temporal trend test and its applicationYarong Xue0Zhenlei Li1Dazhao Song2Xueqiu He3Honglei Wang4Chao Zhou5Jianqiang Chen6Aleksei Sobolev7School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, 100083, ChinaSchool of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, 100083, ChinaSchool of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, 100083, China; Corresponding author.School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, 100083, China; Zhong-an Academy of Safety Engineering, Beijing, 100083, ChinaSchool of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, 100083, ChinaSchool of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, 100083, ChinaChina Energy Group Xinjiang Energy Co., Ltd, Urumqi, 830027, ChinaKhabarovsk Federal Research Center of the Far Eastern Branch of the Russian Academy of Sciences (KhFRC FEB RAS), 51 Turgenev Street, Khabarovsk, 680000, RussiaRockbursts have become a significant hazard in underground mining, underscoring the need for a robust early warning model to ensure safety management. This study presents a novel approach for rockburst prediction, integrating the Mann-Kendall trend test (MKT) and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards. The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts. The MKT is then applied to analyze the real-time trend of each index, with adherence to rockburst characterization laws serving as the warning criterion. By employing a confusion matrix, the warning effectiveness of each index is assessed, enabling index preference determination. Ultimately, the integrated rockburst hazard index Q is derived through data fusion. The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q, surpassing the performance of any individual index. Moreover, the model's adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data, making it suitable for complex underground working environments. By providing an efficient and accurate basis for decision-making, the proposed model holds great potential for the prevention and control of rockbursts. It offers a valuable tool for enhancing safety measures in underground mining operations.http://www.sciencedirect.com/science/article/pii/S1674775523002512RockburstMicroseismicityEarly warningMann-Kendall trend testConfusion matrixMulti-indices fusion |
| spellingShingle | Yarong Xue Zhenlei Li Dazhao Song Xueqiu He Honglei Wang Chao Zhou Jianqiang Chen Aleksei Sobolev A method to predict rockburst using temporal trend test and its application Journal of Rock Mechanics and Geotechnical Engineering Rockburst Microseismicity Early warning Mann-Kendall trend test Confusion matrix Multi-indices fusion |
| title | A method to predict rockburst using temporal trend test and its application |
| title_full | A method to predict rockburst using temporal trend test and its application |
| title_fullStr | A method to predict rockburst using temporal trend test and its application |
| title_full_unstemmed | A method to predict rockburst using temporal trend test and its application |
| title_short | A method to predict rockburst using temporal trend test and its application |
| title_sort | method to predict rockburst using temporal trend test and its application |
| topic | Rockburst Microseismicity Early warning Mann-Kendall trend test Confusion matrix Multi-indices fusion |
| url | http://www.sciencedirect.com/science/article/pii/S1674775523002512 |
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