Citation: | YANG Yong-guo, CHEN Yu-hua, 2009. Chaotic Characteristics and Prediction for Water Inrush in Mine. Earth Science, 34(2): 258-262. |
It is difficult to discover the certainty and randomness of the law of the evolution of the underground water system by only using deterministic method or stochastic method, because the evolution of the system is not only deterministic but also stochastic, due to the effect of such factors as hydrologic geology and mine exploitation.Chaos theory combines both deterministic analysis method and stochastic analysis method.The time series of water inrush in mine are the results of the interaction between the factors of the underground water system in mine and contain the information of this dynamical system.Based on the background analysis of hydrologic geology of the second coal mine in Liuqiao, we obtained the Lyapunov index (0.1427) of the time series of water inrush by modeling and analyzing of the chaotic time series.The Lyapunov index shows that the water inrush of the second coal mine in Liuqiao is of chaotic characteristics.By using the established model, the time series of water inrush in mine from April 2004 to February 2005 was verified, and the results indicate that the chaotic time series analysis method is feasible and highly effective in predicting the water inrush in mine.
Cao, L. Y., 1997. Practical method for determining the minimum embedding dimension of a scalar time series. Physica D, 110 (1-2): 43-50. doi: 10.1016/S0167-2789(97)00118-8
|
Grassberger, P., Procacia, I., 1983. Measuring the strangeness of strange attractors. Physica D, 9 (1-2): 189-208. doi: 10.1016/0167-2789(83)90298-1
|
Lü, J. H., Lu, J. A., Chen, S. H., 2002. Chaotic time series analysis and application. Wuhan University Press, Wuhan, 237 (in Chinese).
|
Packard, N. H., Crutchfield, J. P., Farmer, J. D., et al., 1980. Geometry froma time series. Phys. Rev. Lett., 45 (9): 712-716. doi: 10.1103/PhysRevLett.45.712
|
Reibiec, M. S., 1991. Hydrofracturing of rock as a method of water, mudmand gas inrush hazards in underground coal mining. 4th IMt A, 1 (Yugoslavia).
|
Rosenstein, M. T., Collins, J. J., Deluca, C. J., 1993. A practical method for calculating largest Lyapunov exponents from small data sets. Physica D, 65 (3): 117-134.
|
Shang, P. G., Li, X. W., Santi, K., 2005. Chaotic analysis of traffic time series. Chaos, Solitions & Fractals, 25 (1): 121-128.
|
Tang, L., Yang, Y. G., Xu, Z. J., 2007. Study of nonlinear time series analysis and its use on mine water inrush prediction. Geotechnical Investigation & Surveying, (5): 28-31 (in Chinese with English abstract).
|
Tang, Y. M., Xiao, J., 2006. Condition and mechanism about chaos formation in the evolution process of groundwater system of minning area. Journal of China Coal Society, 31 (1): 45-49 (in Chinese with English abstract).
|
Yang, Y. G., Yu, Z. W., Guo, Z. T., et al., 1996. A study on application of time domain combined model to the prediction of climatic trend based on geological records. Chinese Journal of Geophysics, 39 (1): 37-46 (in Chinese with English abstract).
|
Yang, Y. G., Yuan, J. F., Chen, S. Z., 2006. R/S analysis and its application in the forecast of mine inflows. J. ChinaUniv. of Mining & Tech, 16 (4): 425-428.
|
Zhang, J., Lam, K. C., Yan, W. J., et al., 2004. Time series prediction using Lyapunov exponents in embedding phase space. Computers and Electrical Engineering, 30 (1): 1-15. doi: 10.1016/S0045-7906(03)00015-6
|
吕金虎, 陆君安, 陈士华, 2002. 混沌时间序列分析及其应用. 武汉: 武汉大学出版社.
|
汤琳, 杨永国, 徐忠杰, 2007. 非线性时间序列分析及其在矿井涌水预测中的应用研究. 工程勘察, (5): 28-31. https://www.cnki.com.cn/Article/CJFDTOTAL-GCKC200705006.htm
|
唐依民, 肖江, 2006. 矿区地下水系统演化过程中混沌性态形成的条件及机理. 煤炭学报, 31 (1): 45-49. doi: 10.3321/j.issn:0253-9993.2006.01.010
|
杨永国, 余志伟, 郭正堂, 等, 1996. 基于地质记录用时域组合模型预测气候变化趋势的初步研究. 地球物理学报, 39 (1): 37-46. doi: 10.3321/j.issn:0001-5733.1996.01.005
|