ISSN 1003-8035 CN 11-2852/P
    LI Longcan,WU Xin,LIU Yonghong,et al. Evolution of the characteristic parameters of acoustic emission from deformation to failure of a loose soil slope[J]. The Chinese Journal of Geological Hazard and Control,2024,35(5): 151-159. DOI: 10.16031/j.cnki.issn.1003-8035.202312041
    Citation: LI Longcan,WU Xin,LIU Yonghong,et al. Evolution of the characteristic parameters of acoustic emission from deformation to failure of a loose soil slope[J]. The Chinese Journal of Geological Hazard and Control,2024,35(5): 151-159. DOI: 10.16031/j.cnki.issn.1003-8035.202312041

    Evolution of the characteristic parameters of acoustic emission from deformation to failure of a loose soil slope

    • Loose accumulations are widely present in nature and industrial production, possessing complex mechanical properties and relatively high risks of instability. To investigate their sliding instability process during slope deformation, this study explores the evolution of acoustic characteristics throughout the entire process of loose accumulations, from static state, creep to sliding, based on acoustic emission (AE) technology. The AE characteristic parameters of loose accumulations during the sliding process are analyzed, and the AE evolution stages are divided based on the state changes of loose accumulations. Finally, the AE evolution law of the sliding process of loose accumulations is further verified through particle image velocimetry (PIV) analysis and spectral changes. The results indicate that the ringing count and energy gradually increase with the sliding process, while the b-value gradually decreases. The sliding threshold values for the b-value, ringing count, and energy are 0.2, 5000 counts, and 1500 mV·ms, respectively, with the b-value being more sensitive to state changes in loose accumulations. The spectral centroid experiences a decrease of 30~50 kHz in the early pre-sliding stage, followed by oscillatory changes. The time period of these oscillations corresponds to relatively high ringing count and energy values and relatively low b-values. Furthermore, there is an important “window period” before the sliding of loose accumulations, indicating that AE technology has the potential to identify precursors of loose accumulation landslides.
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