Influence of soil parameters on detecting voids behind a tunnel lining using an impact echo method

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Abstract

Tunnel lining cavities are a common problem that may affect the bearing capacity of the tunnel-supporting structure, as well as the tunnel service life. The impact echo (IE) method can be used to detect voids behind tunnel linings. For a long tunnel, the surrounding rocks/soils are inhomogeneous and anisotropic, with parameters that vary with tunnel mileages. It is interesting to analyse whether alterations of the soil parameters affect the non-destructive test results. A laboratory experiment was performed in this study, in which voids behind a concrete plate, representing the tunnel lining, were designed to model the ineffective contact between the soil and the tunnel. The IE method was employed to inspect the existence of the void using different signal analysis approaches in the time, frequency and time-frequency domains. Furthermore, the fractal box-counting dimension was calculated for the purpose of quantitative evaluation. Different soil parameters and void sizes were considered, and finally, a finite element model was built and parameter analysis was accomplished using the software ABAQUS. The results demonstrated that: (1) A comprehensive analysis of vibration signals in the time, frequency and time-frequency domains was useful for identifying voids, while the box-counting dimension was useful for evaluating voids quantitatively. (2) Soils with large density and Young's modulus differences had a certain influence on void detection, while those with large water content and Poisson's ratio differences had little influence. (3) The box-counting dimension value was stable within the area where the void existed behind the tunnel; when the detection point was beyond twice that of the void dimension, it was difficult to locate the void.

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CITATION STYLE

APA

Ma, M., Cao, R., Niu, C., Zhang, H., & Liu, W. (2019). Influence of soil parameters on detecting voids behind a tunnel lining using an impact echo method. Applied Sciences (Switzerland), 9(24). https://doi.org/10.3390/app9245403

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