Precise transportation control method and system for remediation agent for in-situ remediation of underground water

By combining visual and timing attention neural networks for feature extraction and fusion, combined with multi-region collaborative simulation and edge computing, the accuracy and adaptability of repair agent transport control in groundwater in situ repair is solved, and efficient and reliable repair results are achieved.

CN120406147AActive Publication Date: 2025-08-01JIANGSU ZHONGWU ENVIRONMENTAL PROTECTION IND DEV CO LTD
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Patent Information

Application Number
CN202510537625.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-27
Publication Date
2025-08-01
Estimated Expiration
2045-04-27

AI Technical Summary

Technical Problem

The existing groundwater in-situ repair technology is difficult to achieve precise transportation control of repair agents under complex geological conditions, and there are problems such as insufficient feature extraction accuracy, lack of multi-region coordination mechanisms, and poor optimization strategy adaptability.

Method used

Image data and sensor data are combined with visual attention neural network and timing attention neural network for feature extraction, feature fusion is performed through conditional probability diffusion models, high-precision hydrogeological feature model is generated, and local optimization calculation is performed in a multi-region collaborative simulation environment, transport parameters are verified in combination with Monte Carlo probability search method, and edge computing control nodes are used for real-time data fusion and control.

Benefits of technology

It significantly improves the accuracy of hydrogeological characteristics and the adaptability of optimization strategies, realizes precise transportation control during groundwater in situ repair, and improves repair efficiency and system stability.

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Abstract

The invention provides an accurate transportation control method and system for a remediation agent for in-situ remediation of underground water, and relates to the technical field of underground water pollution remediation, and the method comprises the steps: collecting an image of a drilling rock core of a polluted site and sensor data, extracting features through a visual attention network and a time sequence attention network, and carrying out the feature extraction; the features are input into a conditional probability diffusion model and fused to generate hydrogeologic feature vectors, a high-precision hydrogeologic feature model is constructed in combination with space attention mapping and a generative diffusion model, the high-precision hydrogeologic feature model is input into a multi-region collaborative simulation environment for optimization calculation, and monitoring data are fused through edge calculation nodes. And training the lightweight control model to execute repair medicament transport control.
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