Real-Time Wave Prediction Using Directional Sensor Fusion
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Solution Overview
Problem
Current deterministic sea wave prediction methods are limited by their inability to accurately and efficiently identify directional wave components using xyz measurements and provide real-time predictions, which is crucial for safe and optimal marine operations such as ship landings and wave energy conversion.
Innovation Solution
A wave forecasting framework that utilizes xyz motion data to identify directional wave fields, combines multiple sensor measurements through sensor fusion, and propagates wave predictions in time and space using physics-based models, enabling real-time actionable data for marine operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If higher-order physics-based wave propagation models are used to enhance wave prediction accuracy, then prediction accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the wave field into multiple directional components and processes each component separately through parallel computational channels. This segmentation allows the complex physics-based model to be applied to simpler sub-problems, reducing overall computational complexity while maintaining prediction accuracy for the complete wave field
Solution Approach 2:
The patent applies physics-based wave propagation models selectively to specific directional wave components rather than processing the entire wave field uniformly. This partial action approach focuses computational resources on the most significant wave directions, achieving accurate predictions with reduced computational burden
2Measurement precision
If multiple measurement probes are deployed to accurately identify directional wave components, then measurement accuracy is improved, but system complexity and cost increase
Solution Approach 1:
The patent transitions from spatial segmentation (multiple probes at different locations) to temporal-spectral segmentation (single probe measuring over time and frequency). By analyzing the temporal and spectral characteristics of waves at a single location, the system can identify directional components without requiring multiple spatially distributed probes
Solution Approach 2:
The patent replaces the mechanical approach of deploying multiple physical probes with a computational approach using signal processing and wave theory. A single probe's measurements are processed through algorithms that mathematically decompose the wave field into directional components, substituting computational complexity for physical system complexity
3Measurement precision
If complex wave field identification algorithms are implemented, then prediction accuracy is improved, but real-time processing capability deteriorates
Solution Approach 1:
The patent performs preliminary identification of significant wave components and their directions before applying full physics-based propagation models. By pre-processing the wave data to extract key parameters (frequency, direction, amplitude) using efficient spectral methods, the system prepares the input for faster propagation calculations, enabling real-time processing
Data Source
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AI summary
A method and system for prediction of wave properties include collecting time series data streams from one or more wave measurement devices and processing the data using a wave-prediction algorithm to identify the frequency components of the data and compute wave parameters. The wave-field is propagated in space and time to predict wave height, speed and velocity at a target location. A sliding window approach is used to continuously update the prediction in real-time.