来兴平, 蔡美峰. 大尺度采空区围岩断裂失稳信号数据挖掘及破坏预测分析[J]. 工程科学学报, 2003, 25(5): 394-397. DOI: 10.13374/j.issn1001-053x.2003.05.029
引用本文: 来兴平, 蔡美峰. 大尺度采空区围岩断裂失稳信号数据挖掘及破坏预测分析[J]. 工程科学学报, 2003, 25(5): 394-397. DOI: 10.13374/j.issn1001-053x.2003.05.029
LAI Xingping, CAI Meifeng. Data Mining on Rock Crack Signals in Large Scale Mined-out Area and Damage Prediction Analysis[J]. Chinese Journal of Engineering, 2003, 25(5): 394-397. DOI: 10.13374/j.issn1001-053x.2003.05.029
Citation: LAI Xingping, CAI Meifeng. Data Mining on Rock Crack Signals in Large Scale Mined-out Area and Damage Prediction Analysis[J]. Chinese Journal of Engineering, 2003, 25(5): 394-397. DOI: 10.13374/j.issn1001-053x.2003.05.029

大尺度采空区围岩断裂失稳信号数据挖掘及破坏预测分析

Data Mining on Rock Crack Signals in Large Scale Mined-out Area and Damage Prediction Analysis

  • 摘要: 随着监测技术数字化和信息化程度逐步提高,获得的大尺度采空区围岩损伤演化过程,以及包括各种数据格式的图形、矢量等信息量呈数量级增加.将小波变换、固体断裂非平衡统计和神经网络理论用于对非线性采空区围岩断裂失稳信号进行数据挖掘以及综合分析,有利于正确认识和理解采空区围岩体损伤演化的全过程.

     

    Abstract: With increasing development of digital and communication monitoring techniques, the quantity of obtained information about the damage process of rock mass around large scale mined-out areas is significantly increased. The information includes various figures and vectorgrams in digital form. Data mining and analysis for monitored breakage information from rock mass around mined-out areas using wavelet analysis, non-equilibrium statistics and neural network techniques will be beneficial to correct the understanding of the whole damage process of rock mass around min-out areas.

     

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