Semi-Submersible Heaving Motion Prediction Using Prony Sequence
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Solution Overview
Problem
Current methods for predicting heaving motion parameters of semi-submersible offshore platforms based on heaving acceleration suffer from low precision and information loss due to integration errors and baseline errors from acceleration sensors, especially in severe sea conditions.
Innovation Solution
A method that deduces a motion equation using linear potential flow theory and represents heaving acceleration through a Prony sequence, accounting for noise, low-frequency changes, and baseline drift errors to establish a precise relationship between heaving acceleration and motion parameters, avoiding errors caused by traditional filtering methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional integration methods are used to obtain heaving motion parameters from acceleration data, then the calculation process is simple, but integration errors and baseline errors cause low measurement precision
Solution Approach 1:
The patent introduces a Prony sequence as an intermediary mathematical model to bridge the acceleration data and heaving motion parameters. Instead of directly integrating acceleration (which causes drift errors), the Prony sequence serves as a mediator that represents the acceleration signal in a way that naturally eliminates drift terms while maintaining measurement precision.
Solution Approach 2:
The patent replaces the mechanical integration process with a mathematical transformation using the Prony sequence. Instead of performing time-domain integration which accumulates errors, the method transforms the acceleration data into a Prony series representation, substitutes this into the motion equation, and solves for displacement directly, thereby eliminating the need for error-prone integration operations.
2Measurement precision
If filtering methods are used to remove drift terms from acceleration data, then baseline errors are reduced, but information loss occurs and measurement precision decreases
Solution Approach 1:
The patent extracts and removes only the drift term from the acceleration data representation, while preserving all other useful information. By representing acceleration as a Prony sequence and identifying the drift component separately, the method extracts and eliminates only the harmful drift term without filtering out valid motion information, thus avoiding information loss.
Solution Approach 2:
Instead of applying filters to the acceleration data to remove drift (which causes information loss), the patent inverts the approach by representing the acceleration in terms of a Prony sequence that inherently separates and eliminates drift terms through mathematical transformation. This inversion of the problem-solving approach avoids the need for information-lossy filtering operations.
3Measurement precision
If global positioning system is used to monitor heaving motion, then the system is simple to implement, but sampling efficiency is low and measurement precision is poor
Solution Approach 1:
The patent replaces the global positioning system with an acceleration-based measurement system using Prony sequence analysis. This substitution enables higher sampling efficiency and measurement precision by using acceleration sensors that can operate at higher frequencies and provide more precise data for heaving motion calculation through the Prony series transformation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides high calculation precision and practicality by uniformly representing heaving acceleration with a Prony sequence, removing drift terms, and establishing a direct relationship between heaving acceleration and motion parameters, thus improving prediction accuracy and avoiding information loss.
Implementation Method 1
deduces a motion equation of a structure in a heaving direction based on a linear potential flow theory
Implementation Method 2
establishes the relationship between heaving acceleration and heaving motion parameters of a semi-submersible offshore platform through a Prony sequence
Data Source
AI summary
A method for predicting heaving motion parameters of a semi-submersible offshore platform based on heaving acceleration includes: in heaving motion of a semi-submersible offshore platform, representing heaving acceleration of the semi-submersible offshore platform based on a linear potential flow theory; considering a noise influence of a heaving motion measurement marine environment, a low-frequency influence caused by a slow change of the environment and an influence caused by a baseline drift error of an acceleration sensor, introducing a noise term, a low-frequency change term and a baseline drift error term, and uniformly representing the noise term, the low-frequency change term and the baseline drift error term by a unified Prony sequence; and removing a drift term from uniformly represented heaving acceleration, establishing a relationship between the heaving acceleration and heaving motion parameters in terms of the remaining Prony sequence with the drift term being removed, and estimating the heaving motion parameters.