A slope damage positioning method based on coda wave sensitivity kernel function

By constructing a slope damage localization method based on the wake sensitivity kernel function, and utilizing a distributed monitoring array and a three-dimensional mesh model, the problem of low slope damage localization accuracy in existing technologies is solved. This achieves high-precision imaging and localization of internal slope damage, improving the timeliness of engineering early warning.

CN122199859APending Publication Date: 2026-06-12CHONGQING UNIV +2

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHONGQING UNIV
Filing Date
2026-05-15
Publication Date
2026-06-12

AI Technical Summary

Technical Problem

Existing slope monitoring technologies are unable to effectively identify minute damage within the rock mass in the early stages of disaster incubation, resulting in delays and blind spots in engineering early warning. Existing monitoring methods based on wake signals cannot accurately pinpoint the specific location of damage.

Method used

By constructing a slope damage localization method based on the wake sensitivity kernel function, and utilizing a distributed monitoring array and an engineering site monitoring database, combined with a three-dimensional mesh model and sensitivity kernel function, high-precision imaging and localization of internal rock mass damage can be achieved. This includes data acquisition, preprocessing, mesh generation, sensitivity matrix construction, and damage density calculation.

🎯Benefits of technology

It enables precise location and visualization of microcrack clusters within slopes, improving the accuracy of slope damage location and the timeliness of engineering early warning.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present application relates to the technical field of geological disaster monitoring, and discloses a slope damage positioning method based on a coda sensitivity kernel function, which comprises the following steps: arranging a distributed monitoring array in a rock slope monitoring area, recording node coordinates and collecting and preprocessing data, and storing the data in a database; dividing the monitoring area into a three-dimensional grid, and constructing a grid model that integrates monitoring topological relationships; performing envelope analysis on historical reference waveforms, and constructing a physical model of energy density evolution with propagation distance and time, so as to solve the diffusion and dissipation coefficients of rock mass media; constructing a three-dimensional sensitivity kernel function, and generating a sparse sensitivity matrix; taking damage density as a vector to be solved, and taking decorrelation coefficients as observation vectors, constructing and solving a Tikhonov regularization objective function, and obtaining optimal damage density; finally, three-dimensional hazard thermodynamic map imaging and coordinate calculation are performed, and graded early warning of rock slope damage positioning is realized; the present application improves the precision of slope damage positioning.
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