煤与瓦斯突出动态前兆的非线性特征研究
|
摘要
基于混沌和分形理论,分析了描述煤与瓦斯突出动态前兆非线性特征的方法和指标.针对重要突出前兆之一——采掘工作面前方煤体瓦斯涌出量动态时间序列(简称Q序列),计算分析了其最大Lyapunov指数,二阶Renyi熵和关联维,证明Q序列具有混沌-分形特征.进一步研究表明,工作面有突出危险状态与无突出危险状态相比,其Q序列的多重分维谱Dq表现出明显的差异,Dq-q曲线由负q区向正q区过渡时在q=0附近区域明显变陡,而无突出危险时段Dq-q曲线过渡较平缓,从而说明有突出危险时煤岩瓦斯动力系统的变化更为复杂.研究结果可望为突出危险性预测提供一种新的思路.
Based on chaos and fractal theories,the methods and indices for characterizing the nonlinear patterns of dynamic precursors of coal and gas outburst were analyzed.As one of the main outburst precursors,the dynamic time series of gas emission from excavating face,named as Q series in short,was studied in this paper.Through analyzing the largest Lyapunov exponent,the second-order Renyi entropy and the correlation dimension of Q series,it is proved that Q series possesses chaotic and fractal characteristics.Further study of the multifractal characteristics of Q series shows that when there exists outburst danger at the excavating face,the multifractal spectrum Dq of Q series is remarkably different from that while there is no outburst danger.When there is outburst danger,the curve of Dq vs q obviously appears steep near the point that q equals zero.On the contrary,when there is no outburst danger,the curve of Dq vs q varies gently.Consequently it is indicated that while there exists outburst danger,the evolution of the dynamical system of coal/rock containing gas is more complicated,so that it can be expected that the study will provide a new approach to outburst prediction.
Based on chaos and fractal theories,the methods and indices for characterizing the nonlinear patterns of dynamic precursors of coal and gas outburst were analyzed.As one of the main outburst precursors,the dynamic time series of gas emission from excavating face,named as Q series in short,was studied in this paper.Through analyzing the largest Lyapunov exponent,the second-order Renyi entropy and the correlation dimension of Q series,it is proved that Q series possesses chaotic and fractal characteristics.Further study of the multifractal characteristics of Q series shows that when there exists outburst danger at the excavating face,the multifractal spectrum Dq of Q series is remarkably different from that while there is no outburst danger.When there is outburst danger,the curve of Dq vs q obviously appears steep near the point that q equals zero.On the contrary,when there is no outburst danger,the curve of Dq vs q varies gently.Consequently it is indicated that while there exists outburst danger,the evolution of the dynamical system of coal/rock containing gas is more complicated,so that it can be expected that the study will provide a new approach to outburst prediction.
引文
[1]王显政.煤矿安全新技术[M].北京:煤炭工业出版社,2002.
[2]何学秋.含瓦斯煤岩流变动力学[M].徐州:中国矿业大学出版社,1995.
[3]蒋承林,俞启香.煤与瓦斯突出的球壳失稳机理及防治技术[M].徐州:中国矿业大学,1998.
[4]苏文叔.利用瓦斯涌出动态指标预测煤与瓦斯突出[J].煤炭工程师,1996(5):2-7.SU Wen-shu.Probe into prediction of gas and coaloutbust with dynamic index of gas emission[J].CoalEngineer,1996(5):2-7.
[5]廖明,张文明,方湄,等.时间序列分形特征的判别[J].北京科技大学学报,1998,20(5):412-416.LIAO Ming,ZHANG Wen-ming,FANG Mie,et al.Discriminating fractals in time series[J].Journal ofUniversity of Science and Technology Beijin,1998,20(5):412-416.
[6]郝柏林.分形和分维[J].科学,1986,38(1):9-17.
[7]TAKENS F.Detecting strange attractors in turbu-lence[C]//RAND D,YOUNG L S.Dynamical Sys-tems and Turbulence.Berlin:Springer-Verlag,1981:366-391.
[8]吕金虎,陆君安,陈士华.混沌时间序列分析及其应用[M].武汉:武汉大学出版社,2000.
[9]GRASSBERGER P,PROCACCIA I.Dimensionsand entropies of strange attractors from a fluctua-ting dynamics approach[J].Nonlinear Phenomena,1984,13(1/2):34-54.
[10]洪时中,洪时明.一种客观确定分形“无标度区”的方法:自相似比法[J].大自然探索,1993,12(2):53-57.HONG Shi-zhong,HONG Shi-ming.A new meth-od to determine scaling range of fractals:self-similarratio algorithm[J].Exploration of Nature,1993,12(2):53-57.
[11]朱令人,陈顒.地震分形[M].北京:地震出版社,2000.
[2]何学秋.含瓦斯煤岩流变动力学[M].徐州:中国矿业大学出版社,1995.
[3]蒋承林,俞启香.煤与瓦斯突出的球壳失稳机理及防治技术[M].徐州:中国矿业大学,1998.
[4]苏文叔.利用瓦斯涌出动态指标预测煤与瓦斯突出[J].煤炭工程师,1996(5):2-7.SU Wen-shu.Probe into prediction of gas and coaloutbust with dynamic index of gas emission[J].CoalEngineer,1996(5):2-7.
[5]廖明,张文明,方湄,等.时间序列分形特征的判别[J].北京科技大学学报,1998,20(5):412-416.LIAO Ming,ZHANG Wen-ming,FANG Mie,et al.Discriminating fractals in time series[J].Journal ofUniversity of Science and Technology Beijin,1998,20(5):412-416.
[6]郝柏林.分形和分维[J].科学,1986,38(1):9-17.
[7]TAKENS F.Detecting strange attractors in turbu-lence[C]//RAND D,YOUNG L S.Dynamical Sys-tems and Turbulence.Berlin:Springer-Verlag,1981:366-391.
[8]吕金虎,陆君安,陈士华.混沌时间序列分析及其应用[M].武汉:武汉大学出版社,2000.
[9]GRASSBERGER P,PROCACCIA I.Dimensionsand entropies of strange attractors from a fluctua-ting dynamics approach[J].Nonlinear Phenomena,1984,13(1/2):34-54.
[10]洪时中,洪时明.一种客观确定分形“无标度区”的方法:自相似比法[J].大自然探索,1993,12(2):53-57.HONG Shi-zhong,HONG Shi-ming.A new meth-od to determine scaling range of fractals:self-similarratio algorithm[J].Exploration of Nature,1993,12(2):53-57.
[11]朱令人,陈顒.地震分形[M].北京:地震出版社,2000.
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心