BLASTING, Volume. 38, Issue 2, 37(2021)

Denoising Algorithm of Blasting Signal based on Fourier Decomposition Method-Wavelet Packet Analysis

WANG Hai-long1,*... BAI Hao-bo1, ZHAO Yan2, WANG Bin3 and WANG Hai-jun3 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    In allusion to the issue of the blasting vibration signal containing which a lot of high-frequency noise due to the complex blasting construction environment, a noise reduction method based on Fourier decomposition(FDM) combined wavelet packet threshold method is proposed.Firstly, based on Fourier decomposition theory, blasting vibration signals were decomposed into several Fourier intrinsic band frequency functions(FIBFs).Then, the correlation coefficients between the decomposed modal components and the original signal were calculated respectively, and the dominant modal components were screened out by the correlation coefficient method, the dominant modal components were reconstructed subsequently.Finally, the wavelet packet threshold method was used to further denoise the reconstructed signal, and the final pure blasting vibration signal was obtained.The results show that the new method has the advantages of both Fourier decomposition and wavelet packet analysis.Compared with the existing common methods, the combined denoising method of Fourier decomposition and wavelet packet analysis has the highest signal-to-noise ratio(10.3940) and the minimum root mean square difference(0.0889).The obtained time-history curve is smoothing and the denoising effect is better.It provides a new way to denoise similar blasting vibration signal.

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    WANG Hai-long, BAI Hao-bo, ZHAO Yan, WANG Bin, WANG Hai-jun. Denoising Algorithm of Blasting Signal based on Fourier Decomposition Method-Wavelet Packet Analysis[J]. BLASTING, 2021, 38(2): 37

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    Paper Information

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    Received: Jan. 19, 2021

    Accepted: --

    Published Online: Feb. 2, 2024

    The Author Email: Hai-long WANG (wanghailong-65@163.com)

    DOI:10.3963/j.issn.1001-487x.2021.02.006

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