Application of removal trend method of pattern adapted continuous wavelet to blast vibration signal analysis

Zhang Sheng; Ling Tonghua; Cao Feng; Huang Kan

doi:10.11883/1001-1455(2017)02-0255-07

Volume 37 Issue 2

Mar. 2017

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Zhang Sheng, Ling Tonghua, Cao Feng, Huang Kan. 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. doi: 10.11883/1001-1455(2017)02-0255-07

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Zhang Sheng, Ling Tonghua, Cao Feng, Huang Kan. 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. doi: 10.11883/1001-1455(2017)02-0255-07

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Application of removal trend method of pattern adapted continuous wavelet to blast vibration signal analysis

doi: 10.11883/1001-1455(2017)02-0255-07

Zhang Sheng^{1, 2},
Ling Tonghua^{1
,
,},
Cao Feng¹,
Huang Kan¹

1.
School of Civil Engineering and Architecture, Changsha University of Science & Technology, Changsha 410114, Hunan, China
2.
College of Civil Engineering, Hunan City University, Yiyang 413000, Hunan, China

Received Date: 2014-10-24
Rev Recd Date: 2014-02-04
Publish Date: 2017-03-25

Abstract

Abstract

To accurately characterize such important characteristics as the peak velocity and the energy distribution in different frequency ranges of the blast vibration signal, this signal's trend after the time integral has to be removed. In this paper, the trapezoidal numerical integration of the measured blast vibration acceleration signal was carried out, the blast vibration velocity signal after the time integral as a method for the wavelet basis was proposed, the trend of the blast vibration velocity signal after the time integral was removed using this method, and the characteristics of energy distribution in different frequency ranges of the signal after the trend removal was analyzed. The results show that the trend of the blast vibration velocity signal after the time integral was successfully removed using the pattern adapted wavelet method. Compared with the frequency spectra analysis based on the conventional Fourier transform, the energy analysis based on the wavelet transform had a higher frequency resolution and was more suitable for the analysis that satisfied a higher requirement of frequency resolution for the signal. The more widely divided the different frequency ranges, the higher the degree of the energy distribution correlation in different frequency ranges between the measured blast acceleration signal and the blast vibration velocity signal and, on the other hand, the less widely divided, the lower the degree of the correlation.
- blast vibration,
- energy distribution,
- pattern adapted wavelet,
- trend,
- wavelet basis

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References(16)

References

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