scholarly journals Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices

2018 ◽  
Vol 28 (5) ◽  
pp. 767-774 ◽  
Author(s):  
Linming Dou ◽  
Wu Cai ◽  
Anye Cao ◽  
Wenhao Guo
Keyword(s):  
Rock Burst ◽  
Early Warning

scholarly journals GA-Based Early Warning Method for Rock Burst with Microseismic and Acoustic Emission in Steeply Inclined Coal Seam

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yarong Xue ◽  
Dazhao Song ◽  
Zhenlei Li ◽  
Jianqiang Chen ◽  
Xueqiu He ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Rock Burst ◽  
Coal Mine ◽  
Early Warning ◽  
Characteristic Parameter ◽  
Control Measures ◽  
Risk Level ◽  
Parameter System ◽  
Fitness Value ◽  
Rock Burst Risk

Aiming at problem of low efficacy of early warning of rock burst in coal mine, a multisystem and multiparameter integrated early warning method based on genetic algorithm (GA) is proposed. In this method, firstly, the temporal-spatial-intensity information of energy incubation process of rock burst is deeply mined, and the multidimensional precursory characteristic parameter system of rock burst is constructed. Secondly, the genetic algorithm is used to train the historical monitoring data to obtain the optimal critical value and fitness value of each precursory characteristic parameter, and then the early warning index WC of each monitoring system is calculated. Finally, the integrated rock burst early warning index IC is obtained by synthesizing the early warning index WC of each system. The value of IC corresponds to the specific rock burst risk level of the mine. This method is applied to Wudong coal mine in Xinjiang, China. Based on the actual situation of the mine, a multidimensional precursory characteristic parameter system of rock burst is constructed, which includes energy deviation (DE), frequency ratio (Fr), frequency deviation (DF), degree of dispersion (DS), and total high value of energy deviation (DH). After analyzing the rock burst danger status and risk level in the monitoring area, the early warning capability of this method is found to reach 0.896. Combining with the specific prevention and control measures corresponding to different rock burst risk levels, it can provide effective guidance for the field work.

scholarly journals Study on Rock Burst Early Warning in the Working Face of Deep Coal Mines Based on the Law of Gas Emission

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qinghua Zhang ◽  
Shudong He
Keyword(s):  
Rock Burst ◽  
Early Warning ◽  
Critical Value ◽  
Gas Emission ◽  
Distribution Law ◽  
Deep Mine ◽  
Gas Concentration ◽  
Research Results ◽  
Working Face ◽  
The Law

This study is aimed at predicting rock burst disasters in high gas mines. First, the distribution law and correlation of gas and stress in the F15-17-11111 working face of Pingdingshan No. 13 Mine were analyzed based on the coupling relationship between gas emission and stress in the working face. Next, the relationship between gas emission and stress distribution was revealed, and an early warning method of rock burst in the deep mine working face based on the law of gas emission was proposed and applied to the F15-17-11111 working face. Finally, the critical value of the gas concentration indicator for rock burst early warning in the F15-17-11111 working face was determined as 0.05%. The following research results were obtained. The gas emission and the mining stress in the F15-17-11111 working face are negatively correlated. Mechanically, their correlation satisfies the typical coupling. Besides, the critical value of the gas concentration indicator determined by the proposed early warning method boasts high accuracy in predicting rock burst disasters. It can be used as an early warning method for underground rock burst disasters to promote the safety of working face mining. The research results provide reference and guidance for the monitoring and early warning of rock burst disasters in deep high gas mines.

scholarly journals Application of Data Mining in an Intelligent Early Warning System for Rock Bursts

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 55 ◽  
Author(s):  
Xuejun Zhu ◽  
Xiaona Jin ◽  
Dongdong Jia ◽  
Naiwei Sun ◽  
Pu Wang
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
Rock Burst ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Monitoring Data ◽  
Efficient Production ◽  
Mining Technology ◽  
Rock Bursts

In view of rock burst accidents frequently occurring, a basic framework for an intelligent early warning system for rock bursts (IEWSRB) is constructed based on several big data technologies in the computer industry, including data mining, databases and data warehouses. Then, a data warehouse is modeled with regard to monitoring the data of rock bursts, and the effective application of data mining technology in this system is discussed in detail. Furthermore, we focus on the K-means clustering algorithm, and a data visualization interface based on the Browser/Server (B/S) mode is developed, which is mainly based on the Java language, supplemented by Cascading Style Sheets (CSS), JavaScript and HyperText Markup Language (HTML), with Tomcat, as the server and Mysql as the JavaWeb project of the rock burst monitoring data warehouse. The application of data mining technology in IEWSRB can improve the existing rock burst monitoring system and enhance the prediction. It can also realize real-time queries and the analysis of monitoring data through browsers, which is very convenient. Hence, it can make important contributions to the safe and efficient production of coal mines and the sustainable development of the coal economy.

scholarly journals Pattern Recognition of Signals for the Fault-Slip Type of Rock Burst in Coal Mines

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
X. S. Liu ◽  
J. Tan ◽  
Y. L. Tan ◽  
S. C. Hu
Keyword(s):  
Pattern Recognition ◽  
Electromagnetic Radiation ◽  
Rock Burst ◽  
Early Warning ◽  
Mechanical Model ◽  
Fault Slip ◽  
Coal Face ◽  
Major Threat ◽  
Good Agreement

The fault-slip type of rock burst is a major threat to the safety of coal mining, and effectively recognizing its signals patterns is the foundation for the early warning and prevention. At first, a mechanical model of the fault-slip was established and the mechanism of the rock burst induced by the fault-slip was revealed. Then, the patterns of the electromagnetic radiation, acoustic emission (AE), and microseismic signals in the fault-slip type of rock burst were proposed, in that before the rock burst occurs, the electromagnetic radiation intensity near the sliding surface increases rapidly, the AE energy rises exponentially, and the energy released by microseismic events experiences at least one peak and is close to the next peak. At last, in situ investigations were performed at number 1412 coal face in the Huafeng Mine, China. Results showed that the signals patterns proposed are in good agreement with the process of the fault-slip type of rock burst. The pattern recognition can provide a basis for the early warning and the implementation of relief measures of the fault-slip type of rock burst.

Early-warning of rock burst in coal mine by low-frequency electromagnetic radiation

2020 ◽  
Vol 279 ◽  
pp. 105755 ◽  
Author(s):  
Liming Qiu ◽  
Zhentang Liu ◽  
Enyuan Wang ◽  
Xueqiu He ◽  
Junjun Feng ◽  
...  
Keyword(s):  
Electromagnetic Radiation ◽  
Rock Burst ◽  
Coal Mine ◽  
Early Warning ◽  
Low Frequency

scholarly journals Multiparameter Monitoring and Prevention of Fault-Slip Rock Burst

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Shan-chao Hu ◽  
Yun-liang Tan ◽  
Jian-guo Ning ◽  
Wei-Yao Guo ◽  
Xue-sheng Liu
Keyword(s):  
Rock Burst ◽  
Early Warning ◽  
Large Diameter ◽  
Early Warning Systems ◽  
Fault Slip ◽  
Pressure Relief ◽  
Stick Slip ◽  
Research Results ◽  
Rock Bursts ◽  
Induced Stress

Fault-slip rock burst is one type of the tectonic rock burst during mining. A detailed understanding of the precursory information of fault-slip rock burst and implementation of monitoring and early warning systems, as well as pressure relief measures, are essential to safety production in deep mines. This paper first establishes a mechanical model of stick-slip instability in fault-slip rock bursts and then reveals the failure characteristics of the instability. Then, change rule of mining-induced stress and microseismic signals before the occurrence of fault-slip rock burst are proposed, and multiparameter integrated early warning methods including mining-induced stress and energy are established. Finally, pressure relief methods targeting large-diameter boreholes and coal seam infusion are presented in accordance with the occurrence mechanism of fault-slip rock burst. The research results have been successfully applied in working faces 2310 of the Suncun Coal Mine, and the safety of the mine has been enhanced. These research results improve the theory of fault-slip rock burst mechanisms and provide the basis for prediction and forecasting, as well as pressure relief, of fault-slip rock bursts.

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