An Experimental Investigation on the Relationship between MS Frequency Response and Coal and Gas Outburst

Abstract

Microseismic (MS) frequency response is an important part of high‐efficiency data mining to achieve the aim of coal and gas outburst (CGOB) early warning. Based on the variation pattern of acoustic emission (AE) signal in the coal failure process, the experimental characteristics of MS activity and typical signals CGOB were obtained in this study. First, the AE behavior of coal failure experiment was studied, and an explanation of laws was provided as follows: the fracture behavior of coal sample exhibits certain characteristics of AE response in terms of AE event count, signal amplitude, and frequency; each stage has its own physical meaning during the process of loading test. Based on these laws, CGOB experiments were carried out using a large CGOB physical simulation system with a MS monitoring system. Notching filter and wavelet packet transform technique were used in the denoising and feature extraction of six typical MS events (signals). The features of each stage, including the time‐frequency domain, were extracted and quantitatively expressed. We finally arrive at the following conclusions: (1) CGOB exhibits significantly periodic characteristics, and each CGOB stage corresponds to the significant response characteristics of MS. CGOB presents varying characteristics, such as “valley‐peaks‐valley”. (2) From the incubation stage to happen stage of outburst, the spectrum significantly moved from extremely low frequency (100‐200 Hz) to high‐frequency band (approach to 1600 Hz). During the residual stage, MS frequency manifested the concentration distribution (50 Hz) and offered the advantage of energy concentration. (3) The phenomenon of signal energy also shows the trend of energy transform low to high and to low modes along with the process. Signals total energy distribution (42.81%, 1,437.5‐1,812.5 Hz) in the happen stage are markedly larger than those of events in incubation stage (7.01%) and residual stage (1.44%). The methodology presented in this paper for CGOB signal analysis provides a new method to obtain MS response precursor and predict CGOB disaster. This approach can be useful for rockburst anticipation and control during mining in gas and highly stressed coal mines.