Model Test on Acoustic Emission Monitoring of Loess Slope Failure

The three stages of loess collapse are characterized by notable concealment and sudden onset due to the sudden nature of loess collapse and the prolonged duration of the peristaltic deformation stage. Traditional displacement monitoring methods struggle to detect early signals of instability and failure, leading to poor timeliness in disaster warnings. This project begins by examining non-force field information related to the loess collapse process. It focuses on acoustic emission monitoring and employs model tests to identify effective waveguide rods for monitoring loess collapse. Additionally, the project investigates the evolution anomalies of acoustic emission parameters before and after loess collapse failure, aiming to establish early warning criteria for loess collapse based on acoustic emission. This work provides a theoretical basis for monitoring and early warning of loess collapses. This study evaluates five parameters of the active waveguide system: sensor installation method, filling material, waveguide rod wall thickness, outer wrapping material, and outer wrapping wall thickness. The densities of the filler materials were tested using the optimal parameters derived from the tests to identify the best configurations for active acoustic emission (AE) waveguide systems suitable for monitoring loess collapse. Subsequently, a one-sided connected loess collapse model was employed for indoor tests, integrating real-time AE monitoring with the active waveguide method. This model facilitates the exploration of AE response characteristics during loess collapse and the analysis of destructive forms of loess collapse and time-sequence evolution of AE ringing counts throughout the deformation and destruction process. Results indicate that using filler materials with high elasticity modulus, high compactness, and low Poisson's ratio, along with thin outer wrapping and waveguide rod walls, leads to strong AE signals. As deformation damage of loess collapse intensifies, the number of AE ringing counts notably increases. A rapid rise in cumulative ringing counts can indicate a "sudden increase", or the b-value may stabilize, providing precursor information for loess collapse.