摘要
基于瓦斯涌出时间序列(简称G序列),研究了利用G线图、移动平均线模型和综合法进行煤与瓦斯突出预测的方法。研究表明:G序列G线图法可实时反映瓦斯涌出的细小变化情况,从而可对瓦斯突出前的异常变化特征及时辨识,但是由于瓦斯涌出影响因素复杂,短期内的异常波动并不一定是突出信号,从而容易造成误判。而移动平均线模型以均线系统为基础,通过判别瓦斯涌出浓度在一定时期内的总体变化趋势,揭示煤体中影响煤与瓦斯突出的各因素与突出之间的关系。综合法利用G线图结合移动平均线模型进行突出预测,除G线图和移动平均线本身提供的信息外,结合G线与不同周期的移动平均线的相互穿越发出的一些反转信号,能够更为准确地预报瓦斯突出。
The paper is aimed at introducing a new approach to identifying the precursors of coal-gas outburst based on the time series of gas concentration. To be accurate, our new method has been established on the time series of gas concentration （abbreviation G series） by using G line chart, moving average model and synthesis method. The approach we have proposed has been established and repeatedly tested as well as applied in Jineheng Sihe mine ＂5.20＂ outburst accident, Chongqing Sanshui 1 # coalmine ＂3.30＂outburst roadway and Hebei Fengfeng Dashueun coalmine outburst monitoring data respectively through the analysis of precursor of the outburst. The results show that G line chart method can reflect any small changes of coal and gas outbursts in time, through which the abnormal information variations can timely be recognized before the outbursts take place. However, since the factors of gas emission are highly intricate, the abnormal fluctuations in the short term may not necessarily be the outburst signals, therefore likely to lead to misjudgment. In such a case, more accurate information can be found based on moving the average system, through study of the overall trend of the gas emission in a certain period of time will be able to reveal the relationship between the impact of coal and gas outburst factors and outburst precursors. The advantage of moving average model is that, after several times of smoothening the gas emission data, the accident-ncidence probability of the interference signals can be made to drop. The integration of synthesis method with tracing the G line chart can help to identify prominent preeursor more effectively, for it integrates the antiinterference ability of moving average model and benefits the real-time of G charts. Moreover, it can make use of the information provided by G line chart and moving the average model, to increase the probability of prediction more accurately with the reversal signals given by G line and the different cycles of the average line moving across eac
出处
《安全与环境学报》
CAS
CSCD
北大核心
2011年第3期170-173,共4页
Journal of Safety and Environment
关键词
安全工程
煤与瓦斯突出
瓦斯涌出时间序列
预测
G线图
移动平均线
综合法
safety engineering
coal and gas outburst
G series of gas emission
identification of preeursor
G line chart
moving average line
synthesis method
