Marine Sensor Trajectory Optimization for Accurate Underwater Deployment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for deploying marine sensors underwater lack accuracy due to inadequate consideration of lateral forces caused by asymmetric vortex shedding and viscous effects, leading to significant prediction errors and inaccurate deployment positions.
Innovation Solution
A trajectory optimization method and device that updates multiple control variables iteratively, incorporating kinematics and dynamics models to account for lateral forces and viscous effects, using global and local random walks to optimize the deployment trajectory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If ideal flow assumption is adopted to calculate lifting force, then calculation is simplified, but lifting force is overestimated and accuracy deteriorates
Solution Approach 1:
The patent changes the calculation parameters from ideal flow assumptions to viscous flow parameters, incorporating Reynolds number and viscosity effects to accurately calculate lifting force and drag coefficients, thereby resolving the contradiction between calculation simplicity and accuracy
Solution Approach 2:
The patent replaces the ideal flow theoretical model with a viscous flow numerical model that accounts for water viscosity effects, substituting simplified mechanical assumptions with more accurate fluid dynamics calculations
2Device complexity
If asymmetric vortex shedding is ignored, then model is simplified, but lateral force prediction becomes inaccurate
Solution Approach 1:
The patent extracts and separately models the asymmetric vortex shedding effect from the overall flow field, using vortex strength coefficients to quantify this specific phenomenon, thereby improving lateral force prediction without excessively complicating the entire model
Solution Approach 2:
The patent introduces vortex strength coefficients as intermediary parameters that mediate between the simplified flow model and the complex asymmetric vortex effects, allowing accurate representation of lateral forces through a manageable computational approach
3Ease of operation
If trajectory optimization is not performed, then operation is simpler, but deployment accuracy deteriorates
Solution Approach 1:
The patent performs preliminary trajectory optimization calculations before the actual deployment operation, determining optimal release parameters in advance, which maintains operational simplicity during execution while ensuring high deployment accuracy through pre-computed optimization
Solution Approach 2:
The patent implements feedback mechanisms where trajectory prediction results are used to adjust release parameters, creating an iterative optimization process that improves deployment accuracy while maintaining operational simplicity through automated feedback loops
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 significantly improves the accuracy of three-dimensional trajectory prediction and deployment of marine sensors, accounting for asymmetric vortex shedding and viscous effects, resulting in more precise and reliable underwater deployment operations.
Implementation Method 1
the lateral force caused by asymmetric vortex shedding
Implementation Method 2
ignoring the viscous effect of water
Data Source
AI summary
The disclosure discloses a trajectory optimization method and device for accurately deploying marine sensors under water. The method includes the following steps. 1. Randomly select N sets of initial control variables within a range. 2. Input all of N sets of xi to the sensor's underwater glide kinematics and dynamics models, and calculate the smallest distance between N actual deployment positions and target deployment positions. 3. Determine whether the number of iterative operations is less than the preset value, if yes, perform global random walk and local random walk on N sets of xi, obtain N sets of xi again, and return to step 2; otherwise, go to step 4. 4. Output the control variable xi corresponding to Δs(x)nminmin and the corresponding trajectory as the optimal control variable and optimal trajectory. The disclosure can improve the accuracy of prediction on the underwater three-dimensional trajectory of the marine sensor.