No abstract

Rock burst monitoring of heading face is a weak aspect of rock burst monitoring in China; acoustic emission (AE) monitoring is one of the few monitoring technologies used in heading face, but its target signals are small energy events which are easy to be disturbed. Researchers usually focus on the weak AE events but ignore the microseismic (MS) events (different from AE event and caused by a larger scale of coal fracture), while this kind of events can also reflect the pressure situation of heading face and have higher energy value which may become a better indicator for rock burst monitoring of heading face. So, the basic characteristics of MS events in heading face are studied based on a running vibration signal acquisition system, including the occurrence position, main frequency range, maximum amplitude (MA) range, event duration, and relationship with geological structure. This paper provides a development basis of the monitoring method for rock burst monitoring of heading face by using MS events.

No abstract

The classification of multichannel microseismic waveform is essential for real-time monitoring and hazard prediction. The accuracy and efficiency could not be guaranteed by manual identification. Thus, based on 37310 waveform data of Junde Coal Mine, eight features of statistics, spectrum, and waveform were extracted to generate a complete data set. An automatic classification algorithm based on artificial neural networks (ANNs) has been proposed. The model presented an excellent performance in identifying three preclassified signals in the test set. Operated with two hidden layers and the Logistic activation function, the multiclass area under the receiver operating characteristic curve (AUC) reached 98.6%.

Previously conducted studies have established that mining activities can activate faults, which will cause floor water inrush disasters and cause loss of personnel and property. In order to reduce the possibility of water inrush disasters in mining, it is particularly important to study the dynamic characteristics and rules of floor fault activation under the influence of mining. In this work, firstly, a microseismic monitoring system was established in the working face to analyze the changes of microseismic indexes before and after grouting. It was found that grouting can enhance the strength of a rock mass and play a role in sealing the water channel. Secondly, the quadratic kernel function of microseismic event energy was established. It was found that the accumulation degree of microseismic events and the region of high energy kernel density increased with the decrease of the distance between the working face and the left boundary of the “analysis region”. Combined with a microseismic event index and water inflow, the activation process of the floor fault was divided into five stages. Finally, the plastic failure region of surrounding rock under different excavation steps was analyzed by numerical simulation, and the characteristics of fault activation were further explained. A method of taking measures to prevent water inrush in the “sign stage of fault activation” was proposed.