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[1]于正兴,何学秋,朱权洁,等.基于小波包分形的矿山微震波形特征分析[J].中国安全生产科学技术,2014,10(6):27-32.[doi:10.11731/j.issn.1673-193x.2014.06.004]
　YU Zheng xing,HE Xue qiu,ZHU Quan jie,et al.The wavelet fractal characteristic of microseismic waveinmining[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2014,10(6):27-32.[doi:10.11731/j.issn.1673-193x.2014.06.004]
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基于小波包分形的矿山微震波形特征分析
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
10
期数:
2014年6期
页码:
27-32
栏目:
学术论著
出版日期:
2014-06-30

文章信息/Info

Title:
The wavelet fractal characteristic of microseismic waveinmining
文章编号:
20140604
作者:
于正兴1; 何学秋2; 朱权洁3; 吕垒4
(1 中国安全生产科学研究院, 北京 100012; 2 华北科技学院, 北京 101601; 3 北京科技大学 土木与环境工程学院， 北京 100083；4中钢集团 武汉安全环保研究院，湖北 武汉 430081）
Author(s):
YU Zhengxing1;  HE Xueqiu2;  ZHU Quanjie3;  LV Lei4
(1China Academy of Safety Science and Technology Beijing 100012, China; 2 North China Institute of Science and Technology, Beijing 101601, China; 3 Civil and Environmental Engineering School, University of Science and Technology Beijing, Beijing 100083, China; 4 Wuhan Safety and Environmental Protection Research Institute, Sinosteel Corporation, Wuhan Hubei 430081, China)
关键词:
微地震波形; 小波分形; 分形盒维数; MATLAB; 波形特征
Keywords:
microseismic wave;  wavelet fractal;  box dimension;  MATLAB;  wave characteristic
分类号:
X936
DOI:
10.11731/j.issn.1673-193x.2014.06.004
文献标志码:
A
摘要:
矿山微震波形具有非平稳、非高斯、突发瞬态等特点，使用常规方法很难寻求其特征。通过确立微震波形的分形特性，编制了相应的MATLAB程序求解计算，对矿山微震波形的小波分形特征进行了研究。建立了矿山微震波形的分形计算算法及合理标度；利用小波包方法将微震波形分解为多个频带，选择了（0~64）Hz、（64~96）Hz、（96~128）Hz和（128~256）Hz四个主频带进行研究；建立了四个频带对应的logNk与logk关系拟合曲线，并提取了相应的特征值。结果表明：微震波形具有良好的分形特性，其盒维数的大小在一定程度上与频率的高低相对应；波形主频带S4,2与整个波形的盒维数近似相等。微震波形主频带上的分形特性可以作为该波形的特征，用于不同类型微震波形的分类识别。
Abstract:
The microseismic signal inmine is a kind of discrete linear signal, which is difficult to find its characteristics using conventional methods. In this paper, based on previous studies, the fractal characteristics of the microseismic signals inmine was verified and researched. The microseismic signal was analyzed firstly by the establishing of scalefree interval and the calculating of the boxdimension, and then decomposed by using the wavelet packet theory according to its power spectrum characteristics; Four main frequency bands were selected for further analysis: extracting the reconstructed signal of the bands to calculate the boxcounting dimension. Those bands were S3,0(0-64Hz), S4,2(64-96Hz), and this is the frequency band where the peak of the power spectrum located), S4,3(96-128Hz), and S3,2(128-256Hz); The fitting curve of reconstruction signal corresponding relation between logNk and logk was been drawn, and the corresponding box dimension was extracted. The results showed that the microseismic signal has a good fractal characteristics, the value of the boxcounting dimension to some extent reflects the value of the frequency; and the boxcounting dimension of the main frequency band, S4,2, and the whole signal are approximately equal to each other. In this case, the boxcounting dimension can be used to represent the characteristic of the signal for quantitative recognition of different microseismic signals.

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备注/Memo

备注/Memo:
国家“十二五”科技支撑计划项目(2012BAK09B01),国家科技重大专项项目(2011ZX05040-001)
更新日期/Last Update: 2014-07-28