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The Experimental Investigation on Progressive Deformation of Shear Slip Surface Based on Acoustic Emission Measurements

Arabian Journal for Science and Engineering(2022)

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Abstract
The sliding surface deformation of the soil slope mainly presents progressive failure characteristics, and serial acoustic emission (AE) signals are generated during the deformation process of progressive landslide. Early warning systems for soil slope instability should alert users of slope deformation stage to make the right decision. Thus, a model test aiming at reproducing the typical shear surface deformation of a soil slope is designed. The displacement, AE data and corresponding time–frequency characteristics are comprehensively analyzed to evaluate the progressive deformation behavior. Comparisons with different granular backfills measurements show that cumulative AE count increases proportionally with the shear surface displacement, and the experiments demonstrate that the glass sand backfill exhibits remarkable AE detection characteristics and stronger correlation results. Significantly, AE signal exhibits variant dominant frequencies at different deformation stages, and there is the significant phenomenon that not only the low-frequency signals generated with a significantly increase number, at the same time the continuous high-frequency signals appear during the accelerating deformation stage. Furthermore, from the statistical trend of the energy percentage of the high-frequency band into 312.5–500 kHz, it is found that the correlative energy proportion occupies up to 15%, or even higher during the accelerating stage, indicating that the landslide may be about to enter a severely dangerous stage. This study proposes a new perspective on the frequency characteristics as the early warning index, which can be combined with other traditional acoustic emission indicators to improve the accuracy of the field warning monitoring for the soil progressive landslides.
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Key words
Shear surface deformation,Progressive instability,Acoustic emission data,Dominant frequency,Identification index
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