Intelligent early warning, prevention and control system and method for slope damage of schist reservoir area
By using a data fusion and knowledge base construction module, a hybrid early warning model, and a cloud-edge collaborative deployment platform, the slope damage mechanism knowledge base is dynamically adjusted, which solves the problem of lag in existing early warning systems, realizes early identification of slope damage and closed-loop feedback of prevention and control measures, and improves the accuracy and reliability of the early warning system.
Patent Information
- Application Number
- CN202610430536.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-02
- Publication Date
- 2026-07-24
AI Technical Summary
Existing slope early warning systems rely on static mechanical parameters and purely data-driven models, resulting in delayed early warnings under complex working conditions and a lack of a closed-loop calibration mechanism for disaster prevention and control effects on the underlying algorithms.
By employing a data fusion and knowledge base construction module, combined with a Bayesian update algorithm and a hybrid early warning model, the slope damage mechanism knowledge base is dynamically adjusted. By utilizing chain-based physical criteria and an artificial intelligence time-series prediction network, an early warning logic driven by both mechanism and data is realized. Furthermore, a feedback mechanism for the prevention and control decision support module is implemented through a cloud-edge collaborative deployment platform.
It improves the accuracy and timeliness of early warning, enables early identification of local fracture characteristics inside the rock mass, realizes quantitative assessment of disaster prevention measures and self-calibration of system parameters, and enhances the physical reliability and accuracy of slope damage monitoring.