Slope fusion early warning method and system based on geomechanics and spatial weighting
By combining geomechanics and spatial weighted slope fusion early warning method, and utilizing improved BP neural network and DS evidence theory, embedding the rheological properties of soil and rock mass and the spatial topological location factor of sensor, the accuracy and adaptability issues of sensor data analysis are solved, and high-precision slope instability early warning is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 新疆交通科学研究院有限责任公司
- Filing Date
- 2026-04-29
- Publication Date
- 2026-07-17
AI Technical Summary
In existing slope monitoring technologies, the accuracy and reliability of sensor data analysis are insufficient, early warning methods rely on thresholds of a single sensor, leading to false alarms and missed alarms, algorithm models are disconnected from the physical mechanisms of slopes, cannot adapt to different rock and soil types and geological conditions, and the spatial relationship of sensors is not fully utilized.
Combining geomechanics and spatial weighting, a slope fusion early warning method is developed. By improving the BP neural network and DS evidence theory, the rheological properties of soil and rock and the spatial topological location factors of sensors are embedded to dynamically correct the early warning criteria. A BP neural network based on the rheological properties of soil and rock is constructed to fuse multi-source heterogeneous data.
It significantly improves the accuracy and robustness of slope instability early warning, adapts to different geological conditions, reduces false alarms and missed alarms, and improves the feasibility of engineering projects and the reliability of early warning.
Smart Images
Figure CN122416634A_ABST