Surface Evaluation Using Virtual Polygon Networks
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Solution Overview
Problem
Current methods for evaluating the surface of motor vehicle body components are labor-intensive and costly, particularly during the development of forming tools, where surface flaws can be inadequately detected, leading to production inefficiencies and increased costs.
Innovation Solution
A method involving the creation of a virtual polygon network to approximate the surface of body components, using curvature variables determined by a Weingarten map, which is then processed by an artificial neural network to identify and classify surface flaws, reducing manual inspection and enabling early detection of production issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual surface inspection is used, then surface flaws can be detected, but work effort and production costs increase significantly
Solution Approach 1:
The patent creates a virtual polygon network as a digital copy of the physical body component surface. This virtual model replaces manual inspection by enabling automated processing of surface geometry data, reducing both labor effort and costs while maintaining detection capability
Solution Approach 2:
The patent replaces manual mechanical inspection with an automated system that uses polygon network processing and curvature calculations. The Weingarten map computation and neural network analysis substitute for human eyes and hands, enabling consistent, automated surface evaluation
2Measurement precision
If manual surface inspection is used, then surface flaws can be identified, but production costs increase
Solution Approach 1:
By creating a virtual polygon network representation of the surface, the patent enables cost-effective automated analysis without requiring expensive physical inspection equipment or prolonged manual labor, thereby reducing production costs while maintaining detection accuracy
Solution Approach 2:
The patent transforms surface geometry into mathematical parameters (polygon networks, curvature values, Weingarten maps) that can be processed efficiently by computers. This parameter transformation enables automated, cost-effective analysis that replaces expensive manual inspection processes
3Productivity
If surface evaluation is performed early in development, then production issues can be prevented, but detection accuracy may be insufficient
Solution Approach 1:
The patent enables surface evaluation during the development phase by creating virtual polygon networks from design data before physical production occurs. This preliminary virtual inspection allows potential issues to be identified and corrected early, preventing costly rework later while maintaining adequate detection accuracy through rigorous mathematical analysis
Solution Approach 2:
The patent replaces manual visual inspection with automated computational analysis using polygon networks and curvature calculations. This substitution provides both early detection capability and high measurement precision by using mathematical rigor rather than human judgment
Data Source
AI summary
A method for evaluating the surface of a body component of a motor vehicle is provided. A virtual polygonal network of the surface is generated, at least one variable which characterizes a curvature of the polygonal network at at least one node of the polygonal network is determined, and at least one output variable which characterizes a surface defect of the surface is determined based on the variable which characterizes the curvature using an artificial neural network in order to evaluate the surface.