基于VMD-HHT冲击回波法的隧道衬砌检测技术研究

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Abstract Research purposes: Aiming at the problems of multiple peaks and false frequencies in tunnel lining voiddetection by conventional impact echo method, a genetic algorithm with fuzzy entropy and correlation coefficient as thecomprehensive objective function is proposed to optimize the variational mode decomposition (VMD) of the originalsignal. The marginal spectrum of the signal is calculated based on Hilbert-Huang transform (HHT), and the void detection analysis is carried out accordingly. The inherent defects of the Fourier transform in the analysis of non-stationary impact echo signal are solved, and the data processing method is verified based on the simulation signal and the detection signal of tunnel lining physical model.
Research conclusions: (1)The genetic algorithm with fuzzy entropy and correlation coefficient as the comprehensive objective function effectively realizes the decomposition parameters optimization of VMD, which avoids the contingency caused by artificially setting parameters.(2)VMD can adaptively realize components separation with different dominant frequency of the impact echo signal. Because there is no mode aliasing in the decomposition result, the noise signal can be effectively filtered to improve the data signal-to-noise ratio.(3)The impact echo method based on improved VMD-HHT proposed in this paper can reliably detect the lining thickness owing to the clear and obvious dominant frequency in the detection results. The interference of the improved VMD-HHT method is far less than that of the Fourier transform result, which is not easy to misjudge, and effectively improves the detection accuracy.(4)Since there are errorsin the detection results of lining thickness both by the Fourier transform and VMD-HHT method, it is necessary to conduct a comprehensive comparison in combination with the results of dense tunnel lining to accurately determine whether the lining contains void or not.

Key words： impact echo method lining void detection VMD-HHT genetic algorithm marginal spectrum

Received: 27 May 2022

PACS:

U456.3

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	Articles by authors
	MENG Lu
	WANG Xu
	LU Song
	XIAO Yang

Cite this article:

MENG Lu,WANG Xu,LU Song, et al. Research on Tunnel Lining Void Detection Technology Based on Improved VMD-HHT Impact Echo Method[J]. Journal of Railway Engineering Society, 2023, 40(11): 75-82.

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https://tdgcxb.crec.cn/EN/ OR https://tdgcxb.crec.cn/EN/Y2023/V40/I11/75

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