Methods and apparatus for determining the stability of deep-sea floating platform mooring systems

By constructing a multibody dynamics coupled analysis framework and a data-mechanism dual-driven prediction model, the problem of accuracy in predicting the stability of deep-sea floating platform-mooring cable-anchor system was solved, and efficient assessment and early warning of anchor stability were achieved.

CN122674473APending Publication Date: 2026-09-01BEIJING UNIV OF CHEM TECH +1
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Patent Information

Application Number
CN202610647152.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-12
Publication Date
2026-09-01

AI Technical Summary

Technical Problem

Existing technologies cannot effectively support accurate and efficient prediction and early warning of the long-term stability evolution of deep-sea floating platform-mooring cable-anchor system, especially the anchor piles.

Method used

A multibody dynamic coupling analysis framework for deep-sea floating platform mooring systems is constructed, multibody coupling control equations are generated, and a data-mechanism dual-driven prediction model is formed by combining physical information neural networks and long short-term memory networks. The model is pre-trained and optimized to achieve time-series prediction of lateral displacement and lateral earth pressure of anchor piles.

Benefits of technology

It enables accurate assessment and early warning of anchor pile stability, provides high-precision prediction results in deep-sea environments, and has engineering application value.

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Abstract

The specification relates to the technical field of deep-sea oil and gas development, and specifically discloses a deep-sea floating platform mooring system stability determination method and device, the method comprising: acquiring multi-source heterogeneous data, forming a time series data set based on the multi-source heterogeneous data; constructing a multi-body dynamics coupling analysis framework of the deep-sea floating platform mooring system, generating a multi-body coupling control equation; constructing a data-mechanism dual-driven prediction model; embedding the multi-body coupling control equation as a physical constraint into a loss function of a physical information neural network module, pre-training the physical information neural network module to obtain intermediate characteristic output satisfying a physical law; inputting the intermediate characteristic output and input characteristics in the time series data set into a long short-term memory network module for training; inputting parameters of a to-be-predicted working condition into the trained data-mechanism dual-driven prediction model to obtain a system stability evaluation result. The above scheme can realize quantitative evaluation of system stability.
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