冻结立井爆破振动信号多重分形去趋势波动分析

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振动与冲击 ›› 2020, Vol. 39 ›› Issue (6) : 51-58.

论文

付晓强1,2，杨仁树3，崔秀琴1,2，刘幸1,2，刘纪峰1,2，雷振4

作者信息 +

Multi-fractal detrended fluctuation analysis of the blasting vibration signal in a frozen shaft

FU Xiaoqiang1,2，YANG Renshu3，CUI Xiuqin1,2，LIU Xing1,2，LIU Jifeng1,2，LEI Zhen4

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文章历史 +

摘要

针对基于配分函数的多重分形分析不利于局部标度特性突显的问题，把多重分形去趋势波动分析(MF-DFA)方法引入到爆破振动信号分析领域。研究表明：立井爆破振动信号具有多重分形特征，在周边眼不同装药形式下爆破信号MF-DFA谱和多重分形奇异谱具有显著差异，可作为判别周边装药结构形式的特征参数。MF-DFA谱图及其相关参数可以表征立井不同爆破方案下井壁振动响应状态特征，为炮孔装药结构和装药参数的识别与分类提供了一种有效的方法。

Abstract

Considering that the multi-fractal analysis based on the partition function is not conducive to highlighting the local scale characteristics,the multi-fractal detrended fluctuation analysis (MF-DFA) method was introduced into the field of blasting vibration signal analysis.The results show that the vertical shaft blasting vibration signal has multi-fractal characteristics, the MF-DFA spectrum and multi-fractal singular spectrum have significant diversity for the explosive loading form in the cases of different settlement types of peripheral holes, so, they can be used as characteristic parameters to distinguish the structure form of peripheral charge.The MF-DFA spectrum diagram and related parameters can characterize the vibration response state of the shaft lining under different blasting schemes.The study provides an effective method for the identification and classification of blast hole charge structure and charge parameters.

导出引用

付晓强1,2，杨仁树3，崔秀琴1,2，刘幸1,2，刘纪峰1,2，雷振4. 冻结立井爆破振动信号多重分形去趋势波动分析[J]. 振动与冲击, 2020, 39(6): 51-58

FU Xiaoqiang1,2，YANG Renshu3，CUI Xiuqin1,2，LIU Xing1,2，LIU Jifeng1,2，LEI Zhen4. Multi-fractal detrended fluctuation analysis of the blasting vibration signal in a frozen shaft[J]. Journal of Vibration and Shock, 2020, 39(6): 51-58

参考文献

[1] 李清, 于强, 朱各勇,等. 不同药量的切缝药包双孔爆破裂纹扩展规律试验[J]. 岩石力学与工程学报, 2017, 36(9):2205-2212.
LI Qing,YU Qiang,ZHU Geyong,et al. Experimental study of crack propagation under two-hole slotted cartridge blasting with different amounts of charge[J]. Chinese Journal of Rock Mechanics and Engineering, 2017, 36(9): 2205-2212.
[2] 岳中文, 张士春, 邱鹏,等. 装药结构对切缝药包爆破效果影响的研究[J]. 振动与冲击, 2018(10):27-34.
YUE Zhongwen,ZHANG Shichun,QIU Peng,et al. Influence of charge structures on the slotted cartridge blasting effect. Journal of Vibration and Shock, 2018, 37(10): 27-34.
[3] 谢华刚, 阮怀宁, 吴玲丽,等. 复合型切缝药包机理分析及微差爆破试验[J]. 煤炭学报, 2010, 35(s1):68-71.
XIE Huagang,RUAN Huaining,WU Lingli,et al.Compound slit-charge mechanism analysis and millisecond blasting experiment[J].Journal of China Coal Society,2010, 35(s1):68-71.
[4] 杨招伟, 卢文波, 高启栋,等. 爆破地震波中S波识别方法及其应用[J]. 爆炸与冲击, 2018, 38(1):28-36.
YANG Zhaowei,LU Wenbo,GAO Qidong,et al. A S-wave phase picking method for blasting seismic waves and its application in engineering[J]. Explosion and Shock Waves, 2018, 38(1): 28-36.
[5] 张胜, 凌同华, 曹峰,等. 模式自适应连续小波去除趋势项方法在爆破振动信号分析中的应用[J]. 爆炸与冲击, 2017, 37(2):255-261.
Zhang Sheng,Ling Tonghua,Cao Feng,et al.Application of removal trend method of pattern adapted continuous wavelet to blast vibration signal analysis[J].Explosion
and Shock Waves, 2017, 37(2):255-261.
[6] Ihlen E A F. Introduction to Multifractal Detrended Fluctuation Analysis in Matlab[J]. Front Physiol, 2012, 3(141):1-18.
[7] Kantelhardt J W, Zschiegner S A, Koscielny-Bunde E, et al. Multifractal detrended fluctuation analysis of nonstationary time series[J]. Physica A Statistical Mechanics & Its Applications, 2002, 316(1):87-114.
[8] 林近山, 陈前. 基于多重分形去趋势波动分析的齿轮箱故障特征提取方法[J]. 振动与冲击, 2013, 32(2):97-101.
LIN Jinshan,CHEN Qian.Fault feature extraction of gearboxes based on multifractal detrended fluctuation analysis[J]. Journal of Vibration and Shock,2013, 32(2):97-101.
[9] 王俊丽, 张辰彦, 何红弟,等. 基于MF-DFA的交通流量多重分形研究[J]. 计算机工程与应用, 2016, 52(6):31-34.
WANG Junli, ZHANG Chenyan, HE Hongdi, et al. Multifractal analysis of traffic flow based on MF-DFA. Computer Engineering and Applications, 2016, 52（6）：
31-34.
[10]Zhao H, He S. Analysis of speech signals’ characteristics based on MF-DFA with moving overlapping windows[J]. Physica A Statistical Mechanics & Its Applications, 2016, 442:343-349.
[11] Zhang Z , Wen T , Huang W , et al. Automatic epileptic seizure detection in EEGs using MF-DFA, SVM based on cloud computing.[J]. Journal of X-ray science and technology, 2017, 25(2):261-272.
[12] 熊杰, 陈绍宽, 韦伟,等. 基于多重分形去趋势波动分析法的交通流多重分形无标度区间自动识别方法[J]. 物理学报, 2014, 63(20):99-106.
XIONG Jie,CHEN Shaokuan,WEI Wei,et al.Multi-fractal detrended fluctuation analysis algorithm based identification method of scale-less range for multi-fractal charateristics of traffic flow[J].Acta Physica Sinica, 2014, 63(20):99-106.
[12] 李兆飞, 柴毅, 李华锋. 多重分形去趋势波动分析的振动信号故障诊断[J]. 华中科技大学学报(自然科学版), 2012, 40(12):5-9.
LI Zhaofei,CHAI Yi,LI Huafeng.Diagnosing faults in vibration signals by multi-fractal detrended fluctuation analysis[J].Journal Huazhong Univ.of Sci & Tech.(Natural Science Edition),2012, 40(12):5-9.
[14] 孙斌, 许明飞, 周云龙. 气液两相流波动信号多重分形去趋势波动分析[J]. 工程热物理学报, 2011, 32(5):795-798.
SUN Bin,XU Mingfei,ZHOU Yunlong.Multi-fractal detrended fluctuation analysis of fluctuation signal of gas-liquid two-phase flow[J]. Journal of Engineering Thermophysics, 2011, 32(5):795-798.
[15] 杨仁树, 付晓强, 张世平,等. 基于 EEMD 分形与二次型 SPWV 分布的爆破振动信号分析[J]. 振动与冲击, 2016, 35(22):41-47.
YANG Renshu,FU Xiaoqiang,et al.Analysis of blasting vibration signal based on EEMD fractal and quadratic time-frequency SPWV distribution[J].Journal of Vibration and Shock, 2016, 35(22):41-47.
[16] 李精明, 魏海军, 魏立队,等. 摩擦振动信号的EEMD和多重分形去趋势波动分析[J]. 哈尔滨工程大学学报, 2016, 37(9):1204-1208.
LI Jingming,WEI Haijun,WEI Lidui,et al.Ensemble empirical mode decomposition and multifractal detrended fluctuation analysis of frictional vibration signals[J].Journal of Harbin Engineering University, 2016, 37(9):1204-1208.
[17] 万丽, 邓小成, 王庆飞,等. MF-DFA方法与成矿元素分布特征——以大尹格庄金矿为例[J]. 中国矿业大学学报, 2012, 41(1):133-138.
WAN Li,DENG Xiaocheng,WANG Qingfei,et al.Method of MF-DFA and distribution characteristics of metallogenic elements：example from the Dayln gezhuang gold deposit, China[J].Journal of China University of Mining & Technology, 2012, 41(1):133-138.
[18] 熊庆, 张卫华. 基于MF-DFA与PSO优化LSSVM的滚动轴承故障诊断方法[J]. 振动与冲击, 2015, 34(11):188-193.
XIONG Qing,ZHANG Weihua.Rolling bearing fault diagnosis method using MF-DFA and LSSVM based on PSO[J]. Journal of Vibration and Shock,2015, 34(11):188-193.