![]() ![]() The reflected and transmitted acoustic wave pressure variations are investigated exclusively for a multilayer soil buried tunnel. The tunnel system's 3D finite element model is presented, which contains the tunnel lining, surrounding soil, and the air inside the tunnel and at the ground surface. #SOUND SIPHON DEMO FREE#Ī free air explosion is used as the acoustic wave source. The reflected and transmitted waves' pressure values are measured to evaluate the effects of mechanical characteristics of soil layers, tunnel buried depths, and lining concrete types on the acoustic wave behavior of the tunnel. In addition, a utility line is introduced to the system in different positions related to the main tunnel to investigate its effect on the main tunnel’s acoustic wave behavior. The results indicate that in a multilayer soil structure, the relative position of the soil layers and the tunnel (whether the main tunnel or the utility line) significantly impacts the acoustic pressure value, particularly the transmitted wave pressure. When changing the tunnel buried depth and the lining concrete type, multiple pressure peaks are observed in reflected acoustic wave pressure–time history exclusive to a tunnel surrounded by a multilayer soil structure. The findings can be used to precisely interpret the recorded signals for structural health monitoring and locating underground structures, especially in a media with multilayer soil structures. Targeting the challenge of determining the degree of blockage in buried pipelines and the difficulty of effectively extracting blockage features, a blockage detection method integrating variational mode decomposition (VMD) and information gain is proposed. Acoustic impulse response signals were obtained by deconvolving the output signals of the system, which were then subjected to VMD to obtain 12 components in different frequency ranges. Next, information gain (IG) was introduced to characterize the 12 components quantitatively, through which the components containing rich information about the pipe conditions were selected out. Meanwhile, sound pressure level conversion was performed on the selected components to amplify any changes in the sound field. Finally, the root mean square entropy (RMSE) was calculated to constitute the feature eigenvectors, which were input into Random Forests (RF) classifier for defect identification of pipeline. ![]() As the experimental results demonstrate, the proposed method is capable of determining the degree of blockage effectively in the running state. Meanwhile, it can also eliminate the interference of functional parts such as lateral connections during the identification process, thereby improving the identification accuracy. The present study has shown both theoretical significance and application value in the field of defect detection and recognition. Soil piping leads to land degradation in almost all morphoclimatic regions. However, the detection of soil pipes is still a methodological challenge. Therefore, this study aims at testing ground penetrating radar (GPR) to identify soil pipes and to present the complexity of soil pipe networks. ![]()
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