Sediment deposition prediction and optimization dredging method and system based on AI calculation

CN122113667AActive Publication Date: 2026-05-29CHEC DREDGING

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Applications(China)
Current Assignee / Owner: CHEC DREDGING
Filing Date: 2026-04-21
Publication Date: 2026-05-29

AI Technical Summary

Technical Problem

Traditional dredging projects suffer from data heterogeneity, which makes it impossible to collect and analyze equipment operation data in a unified manner. The lack of an adaptive protocol learning mechanism affects the accuracy of sediment deposition prediction and the timeliness of dredging decisions. Furthermore, it is difficult to balance overall efficiency with local real-time response, resulting in navigation delays, a surge in equipment energy consumption, and sediment spread.

Method used

By employing an AI-based computing approach, data access and standardization are achieved through a multi-protocol conversion gateway. A two-level AI scheduling model is used for dredging control, a digital twin system is used for virtual-real synchronization, and closed-loop correction is used to ensure the accuracy of command execution, enabling seamless access and unified management of multi-brand devices.

Benefits of technology

It has improved the intelligence level of dredging operations, enhanced overall efficiency and adaptability, ensured the accuracy of command execution and system stability, balanced navigation support and operational continuity, and reduced the risk of secondary sedimentation.

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Abstract

The application relates to the technical field of intelligent dredging, and particularly discloses a silt deposition prediction and optimized dredging method and system based on AI calculation, which comprises the following steps: collecting silt deposition correlation data of a target water area and original operation data of multi-brand dredging equipment through a multi-protocol conversion gateway deployed on an edge side; the multi-brand dredging equipment comprises at least two different brands of dredging equipment; and performing protocol analysis and format unification on the original operation data based on a protocol dictionary library through the multi-protocol conversion gateway to generate standardized data. Through multi-protocol adaptive conversion and data standardization, seamless access and unified management of the multi-brand dredging equipment are realized; based on a two-level AI decision model, global optimization and local real-time response are fused, and the overall efficiency and adaptability of dredging operation are significantly improved; combined with digital twinning and closed-loop correction, the accuracy of instruction execution and the stability of the system are ensured.

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