基于多变量监测时序的冲击地压复杂性分析
投稿时间:2014-04-23  修订日期:2015-06-19  点此下载全文
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作者单位E-mail
陶 慧 河南理工大学电气工程与自动化学院 taohui@hpu.edu.cn 
李莹(1978-),女(汉),河南济源人,讲师,主要研究领域为混沌预测和智能计算,邮箱:taohui@hpu.edu.cn。电话:13839170006。 焦作大学计算机学院  
马小平 中国矿业大学信息与电气工程学院  
基金项目:国家自然科学基金(60974126)
中文摘要:考虑到冲击地压监测数据含有噪声且长度有限,基于多变量时间序列重构来计算其关联维数d2以判定系统是否混沌,并描述数据的复杂性。论文对传统G-P算法进行扩展改进以求解多变量时序的d2,用于Lorenz混沌系统表明该方法能弥补数据长度的不足和噪声的影响,提高了d2计算精度。得到不同冲击地压监测时序的d2值表明监测数据具有混沌特性,而且冲击破坏性越强,监测数据越复杂。
中文关键词:冲击地压  多变量时间序列  关联维数  混沌特性
 
Rock Burst Complexity Analysis Based on Multivariate Monitoring Time Series
Abstract:Given that rock burst monitoring data had limited-length and contained noise, their correlation dimension (d2) were computed based on multivariate time-series phase space reconstruction, which would determine whether the system is chaotic and describe data complexity. Traditional G-P algorithm was extended to solve d2 of multivariable time-series, then employing the method to Lorenz chaotic system and the results showed the method can offset data length inadequacy and noise influence thus improving calculation accuracy. The d2 value of different data to monitor Rockburst demonstrated that the data had chaotic characteristic, and the stronger Rock burst damage, the more complex monitoring data was.
keywords:Rock burst  Multivariate time-series  Correlation dimension  Chaotic Characteristic
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