Experimental Study on Remote Non-contact Detection of concrete structure cavities based on Laser Doppler Vibrometry technology and acoustic excitation

Abstract This study investigates a non-contact detection method that combines Laser Doppler Vibrometry (LDV) with acoustic excitation to efficiently identify the locations of cavities within tunnel linings. By comparing the vibration response characteristics of hammer excitation and acoustic excitation, it is found that acoustic excitation is better than traditional hammer excitation in terms of vibration stability, frequency distribution range and non-damaging. The study further examined the vibration behaviour of specimens containing cavities of different sizes, depths, and measurement distances. The results show that the increase of cavity size leads to a significant increase in vibration amplitude and a decrease in bending resonance frequency, while the increase of depth leads to a decrease in vibration amplitude and an increase in characteristic frequency, showing obvious correlation with geometric parameters. Furthermore, in long-distance detection scenarios, while vibration amplitude exhibits exponential decay with distance, the resonance frequency shift remains consistently small. This demonstrates that frequency characteristics can serve as a stable defect identification criterion. Ultimately, velocity analysis enables precise detection of void boundaries, validating the method's effectiveness. This study provides a high-precision, non-contact technical solution for diagnosing hidden defects in concrete structures. Experimental data shows its cavity recognition accuracy rate is notably high, demonstrating significant engineering application value.

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Publication Details

Journal
Civil and Environmental Engineering
Published
2026-06-25
DOI
https://doi.org/10.2478/cee-2027-0002
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Experimental Study on Remote Non-contact Detection of concrete structure cavities based on Laser Doppler Vibrometry technology and acoustic excitation

Honglin Ran, Jie Du, Lin Li, Yi Wei et al.
Civil and Environmental Engineering
Structural Health Monitoring Techniques
article

Experimental Study on Remote Non-contact Detection of concrete structure cavities based on Laser Doppler Vibrometry technology and acoustic excitation

Honglin Ran, Jie Du, Lin Li, Yi Wei, Hongyun Yang, Li Mao, Yuanchen Guo, Zhenhuan Zhu, Tao Fu
article en

Abstract

Abstract This study investigates a non-contact detection method that combines Laser Doppler Vibrometry (LDV) with acoustic excitation to efficiently identify the locations of cavities within tunnel linings. By comparing the vibration response characteristics of hammer excitation and acoustic excitation, it is found that acoustic excitation is better than traditional hammer excitation in terms of vibration stability, frequency distribution range and non-damaging. The study further examined the vibration behaviour of specimens containing cavities of different sizes, depths, and measurement distances. The results show that the increase of cavity size leads to a significant increase in vibration amplitude and a decrease in bending resonance frequency, while the increase of depth leads to a decrease in vibration amplitude and an increase in characteristic frequency, showing obvious correlation with geometric parameters. Furthermore, in long-distance detection scenarios, while vibration amplitude exhibits exponential decay with distance, the resonance frequency shift remains consistently small. This demonstrates that frequency characteristics can serve as a stable defect identification criterion. Ultimately, velocity analysis enables precise detection of void boundaries, validating the method's effectiveness. This study provides a high-precision, non-contact technical solution for diagnosing hidden defects in concrete structures. Experimental data shows its cavity recognition accuracy rate is notably high, demonstrating significant engineering application value.

Civil and Environmental Engineering
Chongqing University of Science and Technology (CN), CCCC Highway Consultants (China) (CN), Chongqing University of Technology (CN), Chongqing Jiaotong University (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 11%
Structural Health Monitoring Techniques
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