Collaborative localization method using analytical and iterative solutions for microseismic/acoustic emission sources in the rockmass structure for underground mining. (1st April 2019) - Dong, Longjun; Zou, Wei; Li, Xibing; Shu, Weiwei; Wang, Zewei
Highlights: The effects of abnormal arrivals were eliminated successfully using the analytical localization method. The temporal and spatial errors caused by premeasured wave velocity were weakened efficiently with TD. An effective collaborative localization method for MS/AE was proposed using analytical and TD methods. The proposed CLMAI is a beneficial complement for the current localization methods of MS/AE. The CLMAI is applicable to MS localization in the rockmass structure of dynamic underground mining. Abstract: The localization of microseismic sources/acoustic emission in the rockmass structure can provide 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-stope. 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.