Shallow cavity disease identification of concrete based on improved variational mode decomposition

ZHAO Weigang1, SHI Zhuang2, YANG Yong1, TIAN Xiushu3, JU Jinghui2, LI Yifan4

Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (14) : 91-102.

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PDF(4982 KB)
Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (14) : 91-102.

Shallow cavity disease identification of concrete based on improved variational mode decomposition

  • ZHAO Weigang1,SHI Zhuang2,YANG Yong1,TIAN Xiushu3,JU Jinghui2,LI Yifan4
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Abstract

The problems of noise interference and component recognition in concrete cavity disease detection in open environment are studied, and a method of acoustic-vibration signal recognition for shallow concrete disease based on optimal variational mode decomposition and free vibration decay rate is proposed. The theoretical model of shallow cavity disease in concrete is established, and the characteristic frequency of the disease and its change rules under different working conditions are simulated. A signal decomposition method based on improved variational mode decomposition (IVMD) is proposed, and the optimized sparrow search algorithm (OSSA) based on Tent Chaos and Cauchy variation optimized is designed to search the key parameters k and of VMD. On the basis of optimal decomposition, IMF identification method of shallow cavity disease based on autocorrelation function graph, correlation coefficient, attenuation coefficient and frequency domain distribution is proposed. The amplitude attenuation of is selected to evaluate the attenuation speed of the characteristic IMF, and the cavity disease identification method based on vibration attenuation characteristics is obtained. The effectiveness of the proposed method is verified by the comparative analysis of embedded disease model experiments. The results show that the decomposition method based on IVMD can effectively reduce the interference of noise and other components, and improve the precision and accuracy of cavity disease identification.

Key words

Disease detection / Optimized sparrow search algorithm / Variational mode decomposition / Time

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ZHAO Weigang1, SHI Zhuang2, YANG Yong1, TIAN Xiushu3, JU Jinghui2, LI Yifan4. Shallow cavity disease identification of concrete based on improved variational mode decomposition[J]. Journal of Vibration and Shock, 2024, 43(14): 91-102

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