HAN Liang, LIU Dianshu, XIN Chongwei, LIANG Shufeng, LING Tianlong, WU Yu, LI Chen. Trend removing methods of vibration signals of deep hole bench blasting in near field[J]. Explosion And Shock Waves, 2018, 38(5): 1006-1012. doi: 10.11883/bzycj-2016-0194
Citation:
HAN Liang, LIU Dianshu, XIN Chongwei, LIANG Shufeng, LING Tianlong, WU Yu, LI Chen. Trend removing methods of vibration signals of deep hole bench blasting in near field[J]. Explosion And Shock Waves, 2018, 38(5): 1006-1012. doi: 10.11883/bzycj-2016-0194
HAN Liang, LIU Dianshu, XIN Chongwei, LIANG Shufeng, LING Tianlong, WU Yu, LI Chen. Trend removing methods of vibration signals of deep hole bench blasting in near field[J]. Explosion And Shock Waves, 2018, 38(5): 1006-1012. doi: 10.11883/bzycj-2016-0194
Citation:
HAN Liang, LIU Dianshu, XIN Chongwei, LIANG Shufeng, LING Tianlong, WU Yu, LI Chen. Trend removing methods of vibration signals of deep hole bench blasting in near field[J]. Explosion And Shock Waves, 2018, 38(5): 1006-1012. doi: 10.11883/bzycj-2016-0194
Based on a large number of measured vibration signals of deep hole bench blasting in near field, this paper has contributed the trend mainly to the nonlinear distortion and the low frequency interference superposition with a large amplitude pulse input. On this basis, the effective monitoring range of test instruments has been chosen as criteria to identify the part of the trend. Using ensemble empirical mode decomposition (EEMD), the wavelet analysis, and other signal analysis methods, a trend elimination method is proposed here, which is based on the combination of the frequency band distribution of each intrinsic mode function component and artificial identification. In addition, a wavelet threshold denoising method is also proposed based on autocorrelation analysis to identify noise characteristics. Examples show that the methods are effective and can be realized by batch pretreatment of blasting signals.
CHEN Yan, LIU Zhe, ZHENG Bin, et al. Study on test signal pre-processing method based on LabVIEW[J]. Foreign Electronic Measurement Technology, 2008, 27(10):4-5, 16. doi: 10.3969/j.issn.1002-8978.2008.10.002
WU Zhaohua, HUANG N E. Ensemble empirical mode decomposition:a noise assisted data analysis method[J]. Advances in Adaptive Data Analysis, 2009, 1(1):1-41.DOI: 10.1142/S1793536909000047
ZHU Yanqin, YANG Xianlin. Several new methods based on wavelet thresholding denoising[J]. Electronic Test, 2008(2):18-22. doi: 10.3969/j.issn.1000-8519.2008.02.005
LI Xibing, ZHANG Yiping, LIU Zhixiang. Wavelet analysis and Hilbert-Huang transform of blasting vibration signal[J]. Explosion and Shock Waves, 2005, 25(6):528-535. doi: 10.3321/j.issn:1001-1455.2005.06.008
XIAO Libo, REN Jianting, YANG Haifeng. Study on vibration signal pre-processing method based on Matlab[J]. Computer Simulation, 2010, 27(8):330-337. doi: 10.3969/j.issn.1006-9348.2010.08.081
HAN Liang, LIU Dianshu, XIN Chongwei, LIANG Shufeng, LING Tianlong, WU Yu, LI Chen. Trend removing methods of vibration signals of deep hole bench blasting in near field[J]. Explosion And Shock Waves, 2018, 38(5): 1006-1012. doi: 10.11883/bzycj-2016-0194
HAN Liang, LIU Dianshu, XIN Chongwei, LIANG Shufeng, LING Tianlong, WU Yu, LI Chen. Trend removing methods of vibration signals of deep hole bench blasting in near field[J]. Explosion And Shock Waves, 2018, 38(5): 1006-1012. doi: 10.11883/bzycj-2016-0194
本站查看
DownLoad:
