Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case Study
A scientific and reasonable microseismic monitoring sensor network is crucial for the prevention and control of rockmass instability disasters. In this study, three feasible sensor network layout schemes for the microseismic monitoring of Sanshandao Gold Mine were proposed, comprehensively consideri...
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MDPI AG
2024-11-01
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| Series: | Mathematics |
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| author | Chenglu Hou Xibing Li Yang Chen Wei Li Kaiqu Liu Longjun Dong Daoyuan Sun |
| author_facet | Chenglu Hou Xibing Li Yang Chen Wei Li Kaiqu Liu Longjun Dong Daoyuan Sun |
| author_sort | Chenglu Hou |
| collection | DOAJ |
| description | A scientific and reasonable microseismic monitoring sensor network is crucial for the prevention and control of rockmass instability disasters. In this study, three feasible sensor network layout schemes for the microseismic monitoring of Sanshandao Gold Mine were proposed, comprehensively considering factors such as orebody orientation, tunnel and stope distributions, blasting excavation areas, construction difficulty, and maintenance costs. To evaluate and validate the monitoring effectiveness of the sensor networks, three layers of seismic sources were randomly generated within the network. Four levels of random errors were added to the calculated arrival time data, and the classical Geiger localization algorithm was used for locating validation. The distribution of localization errors within the monitoring area was analyzed. The results indicate that when the arrival time data are accurate or the error is between 0% and 2%, scheme 3 is considered the most suitable layout; when the error of the arrival time data is between 2% and 10%, scheme 2 is considered the optimal layout. These research results can provide important theoretical and technical guidance for the reasonable design of microseismic monitoring systems in similar mines or projects. |
| format | Article |
| id | doaj-art-63fece4512ba47cb85f9cd6894e99b08 |
| institution | DOAJ |
| issn | 2227-7390 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-63fece4512ba47cb85f9cd6894e99b082025-08-20T02:48:00ZengMDPI AGMathematics2227-73902024-11-011222350010.3390/math12223500Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case StudyChenglu Hou0Xibing Li1Yang Chen2Wei Li3Kaiqu Liu4Longjun Dong5Daoyuan Sun6School of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaSanshandao Gold Mine, Shandong Gold Min Laizhou Co., Ltd., Laizhou 261442, ChinaSanshandao Gold Mine, Shandong Gold Min Laizhou Co., Ltd., Laizhou 261442, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaA scientific and reasonable microseismic monitoring sensor network is crucial for the prevention and control of rockmass instability disasters. In this study, three feasible sensor network layout schemes for the microseismic monitoring of Sanshandao Gold Mine were proposed, comprehensively considering factors such as orebody orientation, tunnel and stope distributions, blasting excavation areas, construction difficulty, and maintenance costs. To evaluate and validate the monitoring effectiveness of the sensor networks, three layers of seismic sources were randomly generated within the network. Four levels of random errors were added to the calculated arrival time data, and the classical Geiger localization algorithm was used for locating validation. The distribution of localization errors within the monitoring area was analyzed. The results indicate that when the arrival time data are accurate or the error is between 0% and 2%, scheme 3 is considered the most suitable layout; when the error of the arrival time data is between 2% and 10%, scheme 2 is considered the optimal layout. These research results can provide important theoretical and technical guidance for the reasonable design of microseismic monitoring systems in similar mines or projects.https://www.mdpi.com/2227-7390/12/22/3500numerical modelmicroseismic monitoringsensor network optimizationerror distribution |
| spellingShingle | Chenglu Hou Xibing Li Yang Chen Wei Li Kaiqu Liu Longjun Dong Daoyuan Sun Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case Study Mathematics numerical model microseismic monitoring sensor network optimization error distribution |
| title | Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case Study |
| title_full | Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case Study |
| title_fullStr | Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case Study |
| title_full_unstemmed | Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case Study |
| title_short | Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case Study |
| title_sort | optimization and numerical verification of microseismic monitoring sensor network in underground mining a case study |
| topic | numerical model microseismic monitoring sensor network optimization error distribution |
| url | https://www.mdpi.com/2227-7390/12/22/3500 |
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