Top-Down Data Interpretation for 3D Model Generation
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Solution Overview
Problem
Current techniques for automatically interpreting design drawings and generating three-dimensional models are limited in extracting complete information and are not versatile or robust, especially when dealing with incomplete or non-structured data, such as 2D-CAD drawings and images, which hinders their application in high-resolution numerical simulations and data integration across multiple data sources.
Innovation Solution
A data interpretation method that automatically grows a tree structure from initial graph nodes, associating elements with parent-and-child relationships to estimate meanings and complement information, allowing for flexible and detailed three-dimensional model generation, and an interpreter for object-oriented programming that performs type conversions based on extension-and-intension relationships to integrate fragmentary data from diverse sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If bottom-up assembly techniques are used to automatically establish 3D models from design drawings, then automation is improved, but interpretation failure spreads throughout the entirety causing collapse of three-dimensionalization
Solution Approach 1:
The patent inverts the conventional bottom-up assembly approach by implementing a top-down interpretation method. Instead of assembling elements from individual lines and characters upward, the system starts with the overall drawing structure and progressively breaks it down into constituent elements, thereby containing interpretation failures within local regions rather than allowing them to propagate throughout the entire model.
Solution Approach 2:
The patent segments the design drawing interpretation process into independent regional units. Each region is interpreted separately with its own local coordinate system and element hierarchy, allowing failures in one segment to be isolated and not affect other segments. This segmentation enables robust automatic model generation even when individual region interpretations fail.
2Manufacturing precision
If CAD systems are used for semi-automatic three-dimensionalization, then model detail is improved, but enormous costs are required and engineer knowledge is needed
Solution Approach 1:
The patent implements self-service by enabling the system to automatically interpret design drawings and generate 3D models without requiring engineer intervention or specialized CAD knowledge. The top-down interpretation method with automatic element recognition and assembly allows the system to perform tasks that previously required human expertise, thereby reducing both operational costs and the need for trained personnel.
Solution Approach 2:
The patent replaces the mechanical CAD system approach with an automated image processing and pattern recognition system. Instead of requiring engineers to manually operate CAD tools, the system uses computer vision algorithms to automatically interpret drawing elements, recognize patterns, and construct 3D models, thereby eliminating the need for specialized CAD knowledge and reducing operational complexity.
3Productivity
If conventional automatic interpretation techniques are used, then processing speed is improved, but complete information extraction is difficult and versatility is limited
Solution Approach 1:
The patent implements universality by creating a multi-functional interpretation system that can handle various types of design drawings and data formats. The top-down interpretation framework is designed to recognize multiple element types (lines, curves, text, hatching patterns) and adapt to different drawing conventions, enabling the system to process diverse data formats while maintaining high processing speed through efficient automated algorithms.
Data Source
AI summary
A data interpretation apparatus including a platform configured to automatically execute type conversion of an object. The platform is provided in a control unit of the data interpretation apparatus, and includes an obtaining unit and an interpretation unit. The obtaining unit obtains input data as the object of the platform. The interpretation unit generates an initial graph with respect to the object, and performs interpretation by automatically growing a graph from the initial graph while executing, as necessary, the type conversion of the object associated with each node of the graph toward extension or toward intension.