CAD Volume Draft Operator Detection in Discrete 3D Models

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Solution Overview

Problem

Current CAD systems lack efficient methods for detecting CAD volume draft operators in discrete 3D models, which are crucial for understanding material distribution and manufacturing processes, especially in mechanical parts design and manufacturing.

Innovation Solution

A computer-implemented method for CAD volume draft operator detection in discrete 3D models, involving segmentation, iterative grouping of segments based on drafting axes and angles, and determination of draft types through profile curve analysis, allowing for the identification of draft surfaces, pads, and pockets.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional CAD systems are used for detecting draft operators, then the detection process is simple, but the detection accuracy and completeness are insufficient

Engineering Contradiction:
Improvedetection accuracyVSAvoidsystem complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The method segments the 3D model surface into multiple triangular facets and groups them based on geometric criteria (draft angle, drafting axis, connectivity) to identify draft operators. This segmentation approach enables accurate detection of draft features by analyzing individual surface elements and their relationships, resolving the contradiction between detection accuracy and system complexity.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The method performs preliminary classification of surface facets into drafted and non-drafted categories based on geometric properties before grouping them into draft operators. This preliminary action simplifies the subsequent detection process and improves accuracy by pre-identifying candidate draft surfaces, thereby managing system complexity while enhancing detection precision.

Inventive Principle:
Principle #10Preliminary action

2Measurement precision

If iterative grouping of segments is performed to accurately identify draft operators, then the detection precision is improved, but the computational time increases

Engineering Contradiction:
Improvedetection precisionVSAvoidcomputational time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The iterative grouping process operates on segmented triangular facets rather than the entire surface, reducing the computational burden at each iteration step. By processing small discrete elements and progressively grouping them, the method achieves high detection precision while managing computational time through efficient incremental processing.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The method performs iterative grouping only on candidate draft surfaces identified through preliminary geometric analysis, rather than processing all surfaces uniformly. This partial action approach focuses computational resources on relevant regions, improving detection precision while minimizing unnecessary computational overhead.

Inventive Principle:
Principle #16Partial or excessive action

3Reliability

If comprehensive segmentation and grouping criteria are applied, then the detection completeness is improved, but the algorithm complexity increases

Engineering Contradiction:
Improvedetection completenessVSAvoidalgorithm complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The algorithm segments the surface into triangular facets and applies multiple grouping criteria (geometric connectivity, draft angle consistency, drafting axis alignment) to ensure complete identification of draft operators. This systematic segmentation and multi-criteria evaluation achieves detection completeness while managing algorithm complexity through structured processing steps.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The grouping algorithm uses universal geometric criteria that can identify various types of draft operators (single-sided, double-sided, varying angles) through a unified framework. This multi-functional approach ensures detection completeness across different draft configurations without requiring separate specialized algorithms for each case.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250021717A1Draft feature detection method
Publication Date: 2025.01.16 DASSAULT SYSTEMES SA
  • US20250021717A1 patent drawing
  • US20250021717A1 patent drawing
  • US20250021717A1 patent drawing

AI summary

A computer-implemented method for CAD volume draft operator detection in a discrete 3D model representing a mechanical part. The method includes obtaining a segmentation of the discrete 3D model, iteratively grouping segments of the segmentation, and determining one or more CAD volume draft operators, each CAD volume draft operator corresponding to a respective group. Two segments of a pair of segments are grouped if: each segment of the pair is a drafted surface and both segments have a same respective drafting axis, and both segments have a same respective draft angle relative to the respective drafting axis, or at least one segment has a zero angle relative to the respective drafting axis; or one segment of the pair is a drafted surface and the other segment is a closing plane.