Adaptive Surface Grid for Body Contour Data Storage
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Solution Overview
Problem
Existing methods for storing real data of a body contour require large memory space or insufficient accuracy, as they often use a fixed surface grid resolution without adaptive capabilities.
Innovation Solution
A method that creates a model surface grid based on CAD data, adapts it to real data by displacing grid points to form a memory surface grid, allowing for varying resolutions and efficient storage with high accuracy, particularly in regions requiring higher detail.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high resolution surface grid is chosen, then the accuracy of the surface grid is improved, but the memory space required increases significantly
Solution Approach 1:
The patent applies local quality by creating an adaptive surface grid where different regions of the component have different resolutions. Critical areas with complex geometry or high importance receive finer grid spacing, while less critical areas use coarser spacing. This allows the system to maintain high measurement precision in important regions without proportionally increasing the overall memory space requirement.
Solution Approach 2:
The patent implements dynamics through adaptive grid generation that adjusts resolution based on local surface characteristics. The grid density is dynamically modified during measurement to concentrate points where needed (complex surfaces, critical features) and reduce points where less detail is required, optimizing the balance between accuracy and data volume.
2Quantity of substance
If a low resolution surface grid is chosen, then the memory space required is reduced, but the accuracy of the surface grid becomes insufficient
Solution Approach 1:
Instead of using uniform low resolution across the entire surface, the patent applies local quality by varying the grid resolution spatially. Critical regions maintain high resolution for accurate measurement, while non-critical regions use lower resolution to reduce memory consumption, thus achieving acceptable accuracy with reduced overall data volume.
Solution Approach 2:
The system dynamically adjusts grid density during the measurement process based on local surface characteristics such as curvature, feature importance, and geometric complexity. This dynamic adaptation ensures that measurement precision is maintained where necessary while reducing data volume in less critical areas.
3Ease of manufacture
If a fixed resolution surface grid is used, then the grid generation process is simplified, but the ability to adapt to different measurement requirements is reduced
Solution Approach 1:
The patent implements dynamic grid generation that automatically adapts to different measurement requirements based on local surface characteristics. The system evaluates geometric features, curvature, and importance of different regions to dynamically determine optimal grid density, providing both simplicity through automation and high adaptability to various measurement scenarios.
Solution Approach 2:
The adaptive grid generation system performs self-service by automatically analyzing the component geometry and determining the optimal grid distribution without requiring manual intervention. The system itself identifies where high resolution is needed and where lower resolution suffices, combining simplicity of operation with adaptive capability.
Data Source
AI summary
The invention relates to a method for storing real data of a real body contour (11) of a body (8). The method comprises the method steps:creating a model surface grid (6) with multiple grid points (7), said model surface grid (6) representing a model body contour (5);manufacturing the body (8) based on the model body contour (5) of the CAD data;determining real data of the manufactured body (8);creating a memory surface grid (15) of the real body contour (11) by means of the computer (3);storing the memory surface grid (15) on a data carrier (19) for further processing of the data.