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<p>Buildings on the slope are inevitably affected by the stability of the slope, and cracks and uneven settlement appear in the building structure during the landslide. The prediction of landslides is very important to the judgment of building safety. To investigate the precursor detection of landslide failures based on acoustic emission (AE) signal, a model test aiming at reproducing the shear surface deformation of typical landslide mode was designed. The evolution characteristics of the AE signals were analyzed in terms of AE count, cumulative AE count, AE correlation diagrams, and time-frequency properties. The test results show that for the progressive deformation mode, the AE count experiences a low-level period, an active period and a rapid increase period, and the distribution of the correlation diagram concentrates in a relatively small scale and then gradually scatters. There are high-frequency signals during the accelerating deformation stage. In laboratory experiments, the gray catastrophe analysis model can effectively predict sliding instability states. The comprehensive use of multiple AE features helps to more accurately identify landslide deformation, providing valuable references for subsequent research.</p>

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The prediction of the progressive deformation mode based on active waveguide-generated acoustic emission

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月10日

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  • Zhihui Wu,
  • Yunlong Sun,
  • Jie Dong,
  • Bo Liu,
  • Yongxin Yu,
  • Lingjun Zhang

摘要

Buildings on the slope are inevitably affected by the stability of the slope, and cracks and uneven settlement appear in the building structure during the landslide. The prediction of landslides is very important to the judgment of building safety. To investigate the precursor detection of landslide failures based on acoustic emission (AE) signal, a model test aiming at reproducing the shear surface deformation of typical landslide mode was designed. The evolution characteristics of the AE signals were analyzed in terms of AE count, cumulative AE count, AE correlation diagrams, and time-frequency properties. The test results show that for the progressive deformation mode, the AE count experiences a low-level period, an active period and a rapid increase period, and the distribution of the correlation diagram concentrates in a relatively small scale and then gradually scatters. There are high-frequency signals during the accelerating deformation stage. In laboratory experiments, the gray catastrophe analysis model can effectively predict sliding instability states. The comprehensive use of multiple AE features helps to more accurately identify landslide deformation, providing valuable references for subsequent research.