An improved method to eliminate modal aliasing and false component in blast vibration signals

LI Qing1, XU Wenlong1, ZHANG Di2, LI Na1, FENG Dandan1

Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (17) : 197-204.

PDF(980 KB)
PDF(980 KB)
Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (17) : 197-204.

An improved method to eliminate modal aliasing and false component in blast vibration signals

  • LI Qing1, XU Wenlong1, ZHANG Di2, LI Na1, FENG Dandan1
Author information +
History +

Abstract

Aiming at limitations of the complementary ensemble empirical mode decomposition (CEEMD) method in dealing with problems of modal aliasing and false components of blast vibration signals, an improved solution correlation CEEMD method was proposed.Firstly, after specially processing a signal’s end point, CEEMD was used to decompose the signal.Secondly, correlation coefficient between each IMF component and the original signal and its frequency spectrum were solved to judge false component.Thirdly, after false components and principal components were added, the solution correlation calculation was done to eliminate modal aliasing.The decomposing results of simulated signals with CEEMD as well as correlation coefficients and energy interpolation calculation showed that the decomposition accuracy of the improved solution correlation CEEMD method is higher than those of EMD and CEEMD to effectively suppress signals’ mode aliasing phenomenon, and avoid energy loss brought by directly processing false components; after this method was applied to decompose a blast vibration signal, the energy proportion of non-main frequency parts in each IMF component is basically kept to be lower; so, the improved method can effectively eliminate modal aliasing and false component phenomenon in blast vibration signals.

Key words

Blasting vibration signal / CEEMD / Decorrelation / Modal aliasing / False component

Cite this article

Download Citations
LI Qing1, XU Wenlong1, ZHANG Di2, LI Na1, FENG Dandan1. An improved method to eliminate modal aliasing and false component in blast vibration signals[J]. Journal of Vibration and Shock, 2019, 38(17): 197-204

References

[1] Huang N E, Shen Z, Long S R, et a1.The Empirical Mode Decompositionand the Hilbert Spectrum for Non-linear and Non-stationary Time Series Analysis[J]. Proceedings of the Royal Society, London: Royal Society, 1998, 454: 903-995
[2] Yang Zhijing,Yang Lihua,Qing Chunmei,et al.A method to eliminate riding waves appearing in the empirical AM/FM demodulation[J]. Digital Signal Processing, 2008, 18:488-504.
[3] 胡爱军,唐贵基,安连锁. 振动信号采集中剔除脉冲的新方法[J]. 振动与冲击,2006,25(1):126-132.
[3]Li Zhinong,He Yongyong,Wu Zhaotong.et al.Sinulation of identification with ARMA model and its application to mac-hine fault diagnosis[J]. Journal of vibration and shock,,2006,25(1):126-132.
[4] 高云超,桑恩方,许继友.分离EMD中混叠模态的新方法[J]. 哈尔滨工程大学学报,2008,29(9): 963-966.
[4] Gao Yunchao,Sang Enfang,Xu Jiyou.A new methord for separating  mixed modes in empirical mode decomposition[J]Jiournal of harbin engineering university,2008,29(9): 963-966.
[5] 周颖涛,周绍骑,姚远航. 减少模态混叠的改进EEMD算法[J]. 重庆理工大学学报(自然科学版),2015,29(1):111-114.
[5] Zhou Yingtao, Zhou Shaoqi,Yao Yuanhang. Improved   ensenble empirical mode decomposition to reduce modal aiasing[J].Journal of Chongqing University of Technology  (Natural Science),2015,29(1):111-114.
[6] 郑近德,程军圣,杨宇. 改进的EEMD算法及其应用研究[J]. 振动与冲击,2013,32(21):21-26
[6] Zheng Jinde,Cheng Junsheng,Yang Yu.Modified EEMD algorthm and iits applications. [J]. Journal of vibration and shock,2013,32(21):21-26
[7] RyanD, James FK. The use of a masking signal to improve empirical mode decomposition[C]. International Conference on Acoustics, Speech, and Signal Processing(ICASSP), IEEE, 2005:485-488.
[8] 赵玲,刘小峰,秦树人,等. 消除经验模态分解中混叠现象的改进掩膜信号法[J]. 振动与冲击,2010,29(9):13-17.
[8] Zhao Lin,Liu Xiaofeng,Qin Shuren.etc.Use of masking signal to improve empirical mode decomposition.[J].Journal of vibration and shock,2010,29(9):13-17.
[9] 凌立鹏,毛毳,李长跃. 一种改进掩膜信号法及其在车桥振动响应信号中的应用[J]. 噪声与振动控制,2015,35(3):153-158.
[9] Ling Lipeng,Mao Cui,Li Changyue.An improved masking signal method and its application in vehica-bridge vibration response signal analysis[J].Noise and Vibration Control,2015,35(3):153-158.
[10] 秦品乐,林焰,陈明. 基于平移不变小波阈值算法的经验模态分解方法[J]. 仪器仪表学报,2008,29(12):2637-2641.
[10] Qin Pingle,Lin Yan,Chen Ming.Empirical mode decomp-osition method based on wavelet with translation invariance algorithm[J].Chinese Journal of Scientific Instrument,2008,29(12):2637-2641.
[11] 黄迪山. 经验模态分解中虚假模态分量消除法[J]. 振动、测试与诊断,2011,31(3):381-384.
[11] Huang Dishan. Effect of  sampling on empirical mode decomposition and correction[J].Journal of Vibration,Measure-ment&Diagnosis,2011,31(3):381-384.
[12] 胡爱军. Hilbert-Huang变换在旋转机械振动信号分析中的应用研究[D]. 华北电力大学(河北), 2008.
[12] Hu Aijun.Research on the application of Hilbert-Huang transform in vibration signal analysis of rotating machinery[D].North China Electric Power University(Hebei),2008
[13] 李纪永,李舜酩,陈晓红,等. 含噪信号经验模式分解虚假分量识别方法[J]. 航空动力学报,2014,29(10):2486-2492.
[13] Li Jiyong,Li Shunming, Chen Xiaohong, et al. Illusive component identification method in noisy signal EMD processing[J].Journal of Aerospace power,2014,29(10):2486-2492.
[14] 韩中合,朱霄珣,李文华. 基于K-L散度的EMD虚假分量识别方法研究[J]. 中国电机工程学报,2012,32(11):112-117.
[14] Han Zhonghe,Zhu Xiaoxun,Li Wenhua.A false component identification method of EMD  based on kullback-leibler divergence[J].Proceedings of the CSEE,2012,32(11):112-117.
[15] 沈路,李俊生,王鸿钧. 改进Hilbert-Huang变换在齿轮故障诊断中的应用[J]. 航空动力学报,2009,24(8):1899-1903.
[15] Shen Lu,Li Junsheng,Wang Hongjun.Application of improved Hilbert-Huang transform method in gear fault diagnosis[J].Journal of aerospace power,2009,24(8):1899-1903.
[16] 林丽,余轮. 基于相关系数的EMD改进算法[J]. 计算机与数字工程,2008,36(12):28-36.
[16] Lin Li,Yu Lun.Improvement on empirical mode decom-position based on correlation coefficient[J].Computer&DigitalEngineering,2008,36(12):28-36
[17] Zhaohua Wu et al.A study of the characteristics of white noise using the empirical mode decomposition method. Proc. Roy. Soc. London, 460A, 1597-1611. 2004.
[18] Yeh Jia-Rong,Shieh Jiann-shing. Complementary ensemble empirical mode ecomposition: A novel noise enhanced data analysis method. Advances in Adaptive Data Analysis. 2(2):135-156,2010.
[19] 张迪.地铁隧道精确延时爆破振动传播规律与控制试验研究[D],中国矿业大学(北京),2016.
[19] Zhang Di. Experimental study on blasting vibration propagation laws and controlling with precise time delay technology in metro tunnel[D],China University of Mining& Technology(Beijing),2016.
[20] 肖瑛,殷福亮. 解相关EMD-消除模态混叠的新方法[J]. 振动与冲击,2015, 34(4):25-29.
[20] Xiao Ying,Yan Fuliang.Decorrelation EMD:A new method of eliminating mode mixing[J]. Journal of vibration and shock.2015, 34(4):25-29.
PDF(980 KB)

535

Accesses

0

Citation

Detail

Sections
Recommended

/