Collaborative localization method using analytical and iterative solutions for microseismic/acoustic emission sources in the rockmass structure for underground mining

被引:151
作者
Dong, Longjun [1 ]
Zou, Wei [1 ]
Li, Xibing [1 ]
Shu, Weiwei [1 ]
Wang, Zewei [1 ]
机构
[1] Cent S Univ, Sch Resources & Safety Engn, 932 Lushan South Rd, Changsha 410083, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Microseismic sources/acoustic emission localization; Analytical solutions; Abnormal arrivals; P-wave velocity; Underground mining; CRUSTAL STRUCTURE; SOURCE LOCATION; WAVE VELOCITY; ARRIVALS; MODEL;
D O I
10.1016/j.engfracmech.2018.01.032
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
The localization of microseismic sources/acoustic emission in the rockmass structure can provide on the basis for determining the potential areas of rockmass instability and rockburst in the underground mining. As the construction environment in deep mining is complex, the abnormal arrivals with different scales of errors may be recorded by the monitoring sensors, which can lead to large errors between the located results and the authentic coordinates. In addition, the average premeasured P-wave velocity through blasting tests (blasts) is widely used in the current localization methods, which are unsuitable for the mining environment with dynamic change of wave velocity in multi-level and multi-scope. To eliminate the effects of abnormal arrivals, the analytical localization method is used to remove abnormal arrivals since it has a stable solution with the high precision when the input data are accurate. To weaken errors induced by the dynamic wave velocity, the iterative solution without the need of premeasured P-wave velocity is used to improve the locating accuracy since it can optimize results using the advantage of multiple sensors. Therefore, a collaborative localization method using analytical and iterative solutions (CLMAI) was proposed, which combined with the arrivals of multi-sensor and inversion of the real-time average wave velocity, to seek the optimal locating results. Firstly, the analytical solutions using 6 sensors in unknown velocity system were resolved. The method to remove abnormal arrivals is developed by solving the logistic probability density function for the analytical solutions of different sensors combinations. Then, the iterative localization method based on the time differences was used to locate source coordinates with clear arrivals. Finally, the CLMAI is verified through locating coordinates of blasts and microseismic events (events) in Kaiyang phosphorous mine. Results show that the CLMAI can not only filter the abnormal arrivals by making use of the characteristic of analytical solutions, but also use the iterative method without premeasured average velocity to improve the locating accuracy significantly. The proposed method is a beneficial complement for the current iterative methods using premeasured velocity, which is applicable to microseismic sources localization under complex abnormal arrivals in the rockmass structure of dynamic underground mining.
引用
收藏
页码:95 / 112
页数:18
相关论文
共 35 条
[1]  
[Anonymous], 7626 USBM RI
[2]  
CARDWELL RK, 1976, B SEISMOL SOC AM, V66, P1965
[3]   CRUSTAL STRUCTURE MODELING OF EARTHQUAKE DATA .1. SIMULTANEOUS LEAST-SQUARES ESTIMATION OF HYPOCENTER AND VELOCITY PARAMETERS [J].
CROSSON, RS .
JOURNAL OF GEOPHYSICAL RESEARCH, 1976, 81 (17) :3036-3046
[4]   Discriminant models of blasts and seismic events in mine seismology [J].
Dong, Long-Jun ;
Wesseloo, Johan ;
Potvin, Yves ;
Li, Xi-Bing .
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES, 2016, 86 :282-291
[5]   Three-dimensional analytical solution of acoustic emission source location for cuboid monitoring network without pre-measured wave velocity [J].
Dong, Long-jun ;
Li, Xi-bing ;
Zhou, Zi-long ;
Chen, Guang-hui ;
Ma, Ju .
TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA, 2015, 25 (01) :293-302
[6]   Theoretical and Experimental Studies of Localization Methodology for AE and Microseismic Sources Without Pre-Measured Wave Velocity in Mines [J].
Dong, Longjun ;
Sun, Daoyuan ;
Li, Xibing ;
Du, Kun .
IEEE ACCESS, 2017, 5 :16818-16828
[7]   Three Dimensional Comprehensive Analytical Solutions for Locating Sources of Sensor Networks in Unknown Velocity Mining System [J].
Dong, Longjun ;
Shu, Weiwei ;
Li, Xibing ;
Han, Guangjie ;
Zou, Wei .
IEEE ACCESS, 2017, 5 :11337-11351
[8]  
[董陇军 Dong Longjun], 2017, [岩石力学与工程学报, Chinese Journal of Rock Mechanics and Engineering], V36, P186
[9]   Discrimination of Mine Seismic Events and Blasts Using the Fisher Classifier, Naive Bayesian Classifier and Logistic Regression [J].
Dong, Longjun ;
Wesseloo, Johan ;
Potvin, Yves ;
Li, Xibing .
ROCK MECHANICS AND ROCK ENGINEERING, 2016, 49 (01) :183-211
[10]   Performance and feasibility analysis of two microseismic location methods used in tunnel engineering [J].
Feng, Guang-Liang ;
Feng, Xia-Ting ;
Chen, Bing-Rui ;
Xiao, Ya-Xun .
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2017, 63 :183-193